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Initial blood storage experiment

The design of the Initial Blood Storage Experiment (IBSE) was based upon a carefully controlled comparison between identical sets of human blood cell suspensions - red cells, white cell, and platelets - one set of which was transported aboard the Columbia on a 6 day 11 hour mission, and the other held on the ground. Both sets were carried inside stainless steel dewars within specially fabricated flight hardware. Individual bags of cell suspensions were randomly assigned with respect to ground vs orbit status, dewar chamber, and specific location within the dewar. To foster optimal preservation, each cell type was held under specific optimal conditions of pH, ionic strength, solute concentration, gas tension, and temperature. An added variable in this initial experiment was provided by the use of three different polymer/plasticizer formulations for the sealed bags which held the blood cells. At termination of the experiment, aliquots of the suspensions, identified only by code, were distributed to be assayed. Assays were selected to constitute a broad survey of cellular properties and thereby maximize the chances of detection of gravitational effects. A total of 74 different outcome measurements were reported for statistical analysis. When the measurements were completed, the results were entered into the IBSE data base, at which time the data were matched with the original blood bag numbers to determine their status with respect to polymer/plasticizer type, orbit status (orbit or ground), and storage position within the experimental hardware. The data were studied by analysis of variance. Initially, type of bag and orbital status were main factors; later more detailed analyses were made on specific issues such as position in the hardware and specific plastic. If the analysis of variance indicated a statistical significance at the 5 percent level the corresponding p-value was reported.

Surgenor, Douglas MACN.↗

Biophysical model of eelgrass and water quality in Coos Bay, OR shows greater mitigation potential for ocean acidification than hypoxia

Seagrass beds provide important ecosystem services and are valued, in part, for their potential to mediate stressors such as ocean acidification and hypoxia (OAH) for sensitive species. However, the susceptibility of seagrasses to anthropogenic impacts and recent declines motivate the need to better understand the drivers of seagrass and the water quality consequences that occur with variation in seagrass abundance. To meet this need, we leveraged existing monitoring data (water quality and seagrass), hydrodynamic circulation model, and biogeochemical model framework with seagrass submodel, to produce a biophysical model of Coos Bay estuary, Oregon, U.S. The model includes biogeochemical processes involving water quality, plankton, seagrass, and sediment-water interactions. Ecosystem models like this are useful for evaluating complex estuarine systems because they allow us to extend our understanding of system dynamics beyond existing observations and perform experiments to identify the processes driving observed patterns. We used the biophysical model of Coos Bay to evaluate the dynamics of water quality and native eelgrass (Zostera marina) under three eelgrass abundance scenarios (zero eelgrass, current extent, and maximum observed extent) to elucidate the relationship between eelgrass and OAH. Including eelgrass in the Coos Bay model produced results that more closely resembled water quality observations - dissolved oxygen (DO) and pH were more dynamic in simulations with eelgrass, often having both higher highs and lower lows. While there were some areas of the estuary where DO improved with the addition of eelgrass to the model there was overall a small net increase in harmful DO conditions (based on a salmon physiological threshold). In contrast, ocean acidification conditions, pH and calcium carbonate saturation state for aragonite (Ω), were improved (based on oyster requirements) with the addition of eelgrass - although the magnitude of improvement differed seasonally and spatially. Our new model represents a useful tool - one which accounts for and controls the relevant physical and biogeochemical processes - to evaluate conditions that confer resilience or enhance vulnerability to OAH in an important Pacific Northwest coastal estuary and results can inform the OAH-related dynamics occurring in other eastern boundary current estuaries.

FVCOM-ICM↗

Quality comparison of hydroponic tomatoes (Lycopersicon esculentum) ripened on and off vine

There is a general belief that the quality of tomatoes ripened on vine is better than tomatoes ripened off the vine, influencing among other parameters, the price of this commodity. We compared the quality of hydroponic tomatoes ripened on and off vine by chemical, physical, and sensory evaluation to find what attributes are affected and to what extent. Lycopene, beta-carotene, total and soluble solids, moisture content, ascorbic acid, acidity, pH, texture, and color were analyzed. Tomatoes ripened on vine had significantly more lycopene, beta-carotene, soluble and total solids, higher a* and lower L*, and were firmer. However, a 100-judge panel rated only the color and overall liking of the vine-ripened tomatoes as more intense than the fruit ripened off vine. Therefore, the chemical and physical differences were mostly not large enough to influence the panelist's perception. The characterization of tomatoes ripened on and off vine may help to guide post-harvest handling and treatment and to improve the quality of tomatoes ripened off vine.

Non-NASA Center↗

A Novel Approach to Fast Calculation of High-Order Q-Cumulants

The method of Q-cumulants has been shown as a powerful tool to study the fine details of the azimuthal anisotropies in high-energy nucleus-nucleus collisions. A new method for the fast calculation of arbitrary order Q-cumulant $v_{n}\{2k\}$ values, based on the partition of a non-negative integer l $\le$ m for calculation of the 2m-particle azimuthal correlations is presented in this paper. Unlike the standard Q-cumulants method in which the calculation of high-order multi-particle calculations is impractical, the newly proposed method enables easy calculation. The validity of the method is proven via a toy model that uses the elliptic power distribution to simulate anisotropic emission of particles. The method enables the study of fine details of the $v_{2}$ distribution, such as higher-order central moments of the $v_{2}$ distribution, as well as the hydrodynamic behavior of the Quark-Gluon Plasma.

FOS: Physical sciences↗

Optimizing enzymes for plastic upcycling using machine learning design and high throughput experiments

Plastic use is ubiquitous in the modern world, and polyethylene terephthalate (PET) is one of the most abundantly produced plastics (and the most highly produced polyester), with ~65 million metric tons manufactured annually. To the consumer, PET is likely most recognizable as the plastic used to make beverage bottles. Like many plastics, traditional mechanical or chemical means of PET deconstruction and upcycling are costly and inefficient. Because of these challenges, recycled plastic is generally of lower quality and is more expensive to produce than virgin plastic derived from petroleum. Ultimately, this results in most plastic ending up as waste. We view plastic waste as an underutilized resource which, with the development of more efficient and high-quality recycling processes, could (1) generate significant economic value while (2) decreasing petroleum usage and greenhouse gas emissions, as well as (3) minimizing its negative environmental and health impacts. Biocatalytic recycling, or biomanufacturing the basic building blocks of new plastic from plastic waste, is a promising approach to plastic reuse that complements existing recycling technologies. Recently, biological enzymes capable of breaking down PET have garnered significant attention as an attractive means of dealing with the plastic problem. These enzymes are currently undergoing pilot studies for implementation in industrial-scale enzyme-based recycling. However, there are significant limitations to current enzymes, including the need to perform costly pre-processing of the plastic waste before the enzymes are able to work. Further optimization of these enzymes is necessary to make these technologies competitive, and ultimately incentivise industry-wide adoption of this biology-based green recycling technology. n this work we demonstrate a means to design and generate performant biological enzymes, capable of efficiently deconstructing plastic waste. Specifically, we applied recent advances in artificial intelligence, machine learning, and statistical analysis to design new versions and discover natural enzymes capable of breaking down PET. We focused on optimizing key properties that are important for industrial-scale enzymatic recycling such as pH and thermotolerance. Normal testing of enzymatic plastic-deconstruction is extremely labor intensive and so through this work we also developed a robotic-assisted experimental pipeline capable of characterizing thousands of candidate enzymes. The results of this iterative, AI-guided, multi-discipline approach have led to increases in enzymatic breakdown of over 150X over starting enzymes. This work supports the rapidly developing and transformative field of biocatalytic solutions to environmental problems beyond the discovery and predictive understanding of enzymes for polymer recycling, and has wide implications for tackling numerous energy problems such as carbon capture and fixation (e.g., engineering carbon monoxide dehydrogenase and the rubisco-pathway), biomining (e.g., design of lanthanide-binding proteins) and biomanufacturing (e.g., lignin-deconstruction enzymes).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Insights into the Martian Regolith from Martian Meteorite Northwest Africa 7034

Everything we know about sedimentary processes on Mars is gleaned from remote sensing observations. Here we report insights from meteorite Northwest Africa (NWA) 7034, which is a water-rich martian regolith breccia that hosts both igneous and sedimentary clasts. The sedimentary clasts in NWA 7034 are poorly-sorted clastic siltstones that we refer to as protobreccia clasts. These protobreccia clasts record aqueous alteration process that occurred prior to breccia formation. The aqueous alteration appears to have occurred at relatively low Eh, high pH conditions based on the co-precipitation of pyrite and magnetite, and the concomitant loss of SiO2 from the system. To determine the origin of the NWA 7034 breccia, we examined the textures and grain-shape characteristics of NWA 7034 clasts. The shapes of the clasts are consistent with rock fragmentation in the absence of transport. Coupled with the clast size distribution, we interpret the protolith of NWA 7034 to have been deposited by atmospheric rainout resulting from pyroclastic eruptions and/or asteroid impacts. Cross-cutting and inclusion relationships and U-Pb data from zircon, baddelleyite, and apatite indicate NWA 7034 lithification occurred at 1.4-1.5 Ga, during a short-lived hydrothermal event at 600-700 C that was texturally imprinted upon the submicron groundmass. The hydrothermal event caused Pb-loss from apatite and U-rich metamict zircons, and it caused partial transformation of pyrite to submicron mixtures of magnetite and maghemite, indicating the fluid had higher Eh than the fluid that caused pyrite-magnetite precipitation in the protobreccia clasts. NWA 7034 also hosts ancient 4.4 Ga crustal materials in the form of baddelleyites and zircons, providing up to a 2.9 Ga record of martian geologic history. This work demonstrates the incredible value of sedimentary basins as scientific targets for Mars sample return missions, but it also highlights the importance of targeting samples that have not been overprinted by metamorphic processes, which is the case for NWA 7034.

McCubbin, Francis M.↗

Microgravity Transport Phenomena Experiment (MTPE) Overview

The Microgravity Transport Phenomena Experiment (MTPE) is a fluids experiment supported by the Fundamentals in Biotechnology program in association with the Human Exploration and Development of Space (BEDS) initiative. The MTP Experiment will investigate fluid transport phenomena both in ground based experiments and in the microgravity environment. Many fluid transport processes are affected by gravity. Osmotic flux kinetics in planar membrane systems have been shown to be influenced by gravimetric orientation, either through convective mixing caused by unstably stratified fluid layers, or through a stable fluid boundary layer structure that forms in association with the membrane. Coupled transport phenomena also show gravity related effects. Coefficients associated with coupled transport processes are defined in terms of a steady state condition. Buoyancy (gravity) driven convection interferes with the attainment of steady state, and the measurement of coupled processes. The MTP Experiment measures the kinetics of molecular migration that occurs in fluids, in response to the application of various driving potentials. Three separate driving potentials may be applied to the MTP Experiment fluids, either singly or in combination. The driving potentials include chemical potential, thermal potential, and electrical potential. Two separate fluid arrangements are used to study membrane mediated and bulk fluid transport phenomena. Transport processes of interest in membrane mediated systems include diffusion, osmosis, and streaming potential. Bulk fluid processes of interest include coupled phenomena such as the Soret Effect, Dufour Effect, Donnan Effect, and thermal diffusion potential. MTP Experiments are performed in the Microgravity Transport Apparatus (MTA), an instrument that has been developed specifically for precision measurement of transport processes. Experiment fluids are contained within the MTA fluid cells, designed to create a one dimensional flow geometry of constant cross sectional area, and to facilitate fluid filling and draining operations in microgravity. The fluid cells may be used singly for bulk solutions, or in a Stokes diaphragm configuration to investigate membrane mediated phenomena. Thermal and electrical driving potentials are applied to the experiment fluids through boundary plates located at the ends of the fluid cells. In the ground based instrument, two constant temperature baths circulate through reservoirs adjacent to the boundary plates, and establish the thermal environment within the fluid cells. The boundary plates also serve as electrodes for measurement and application of electrical potentials. The Fluid Manipulation System associated with the MTA is a computer controlled system that enables storage and transfer of experiment fluids during on orbit operations. The system is used to automatically initiate experiments and manipulate fluids by orchestrating pump and valve operations through scripted sequences. Unique technologies are incorporated in the MTA for measurement of fluid properties. Volumetric Flow Sensors have been developed for precision measurement of total fluid volume contained within the fluid cells over time. This data is most useful for measuring the kinetics of osmosis, where fluid is transported from one fluid cell to another through a semipermeable membrane. The MicroSensor Array has been designed to perform in situ measurement of several important fluid parameters, providing simultaneous measurement of solution composition at multiple locations within the experiment fluids. Micromachined sensors and interface electronics have been developed to measure temperature, electrical conductivity, pH, cation activity, and anion activity. The Profile Refractometer uses a laser optical system to directly image the fluid Index of Refraction profile that exists along the MTA fluid cell axis. A video system acquires images of the RI profile over time, and records the transport kinetics that occur upon application of chemical, thermal, or electrical driving potentials. Image processing algorithms have been developed to analyze the refractometer images on a pixel by pixel basis, calibrating and scaling the measured Index of Refraction profile to correlated solution properties of interest such as density, concentration, and temperature. Additional software has been developed to compile the processed images into a three dimensional matrix that contains fluid composition data as a function of experiment time and position in the fluid cell. These data are combined with data from the other sensor systems, and analyzed in the context of transport coefficients associated with the various transport phenomena. Analysis protocols have been developed to measure the transient kinetics, and steady state distribution of fluid components that occur in response to the applied driving potentials. The results are expressed in terms of effective transport coefficients. Experiments have been performed using a variety of solutes, and results generated are that are in agreement with published transport coefficient values.

Mason, Larry W.↗

Prototype development and test results of a continuous ambient air monitoring system for hydrazine at the 10 ppb level

A Hydrazine Vapor Area Monitor (HVAM) system is currently being field tested as a detector for the presence of hydrazine in ambient air. The MDA/Polymetron Hydrazine Analyzer has been incorporated within the HVAM system as the core detector. This analyzer is a three-electrode liquid analyzer typically used in boiler feed water applications. The HVAM system incorporates a dual-phase sample collection/transport method which simultaneously pulls ambient air samples containing hydrazine and a very dilute sulfuric acid solution (0.0001 M) down a length of 1/4 inch outside diameter (OD) tubing from a remote site to the analyzer. The hydrazine-laden dilute acid stream is separated from the air and the pH is adjusted by addition of a dilute caustic solution to a pH greater than 10.2 prior to analysis. Both the dilute acid and caustic used by the HVAM are continuously generated during system operation on an "as needed" basis by mixing a metered amount of concentrated acid/base with dilution water. All of the waste water generated by the analyzer is purified for reuse by Barnstead ion-exchange cartridges so that the entire system minimizes the generation of waste materials. The pumping of all liquid streams and mixing of the caustic solution and dilution water with the incoming sample are done by a single pump motor fitted with the appropriate mix of peristaltic pump heads. The signal to noise (S/N) ratio of the analyzer has been enhanced by adding a stirrer in the MDA liquid cell to provide mixing normally generated by the high liquid flow rate designed by the manufacturer. An onboard microprocessor continuously monitors liquid levels, sample vacuum, and liquid leak sensors, as well as handles communications and other system functions (such as shut down should system malfunctions or errors occur). The overall system response of the HVAM can be automatically checked at regular intervals by measuring the analyzer response to a metered amount of calibration standard injected into the dilute acid stream. The HVAM system provides two measurement ranges (threshold limit value (TLV): 10 to 1000 parts per billion (ppb)/LEAK: 100 ppb to 10 parts per million (ppm)). The LEAK range is created by dilution of the sulfuric acid/hydrazine liquid sample with pure water. This dual range capability permits the analyzer to quantify ambient air samples whose hydrazine concentrations range from 10 ppb to as high as 10 ppm. The laboratory and field prototypes have demonstrated total system response times on the order of 10 to 12 minutes for samples ranging from 10 to 900 ppb in the lLV mode and is greater than 2 minutes for samples ranging from 100 to 1300 ppb in the LEAK mode. Service intervals of over 3 months have been demonstrated for continuous 24 hour/day, 7 day/week usage. The HVAM is made up of a purged cabinet that contains power supplies, RS422 signal transmission capabilities, a UPS, an on-site warning system, and a Line Replaceable Unit (LRU). The LRU includes all of the liquid flow system, the analyzer, the control/data system microprocessor and assorted flow and liquid-level sensors. The LRU is mounted on a track slide system so it can be serviced inplace or totally removed and quickly exchanged with another calibrated unit, thus minimizing analyzer downtime. Once an LRU is removed from an analyzer enclosure, it can be brought to a laboratory facility for complete calibration and periodic maintenance.

Meneghelli, Barry↗

Amine Structure Governs Corrosion Rates of Copper Catalysts in Electrochemical Reactive Capture of CO 2

Reactive capture of CO 2 (RCC) offers an integrated approach that combines CO 2 capture with its direct electrochemical conversion, eliminating the need for CO 2 release from the capture agent. By avoiding the pH, pressure, and temperature swings required for the release step, RCC has the potential to reduce both energy consumption and capital costs compared to the conventional sequential process of CO 2 capture, release, concentration, and conversion. Amines, widely used in industrial CO 2 capture, face challenges in RCC systems due to their incompatibility with transition metal catalysts as well as their tendency to promote electrode corrosion and parasitic hydrogen evolution. Identifying suitable combinations of amines and catalysts is therefore critical to enabling integrated CO 2 capture and conversion. Here, this work systematically investigates the performance of four primary and four secondary amines for RCC on polycrystalline Cu catalysts. Among the eight tested amines, only dimethylamine showed no measurable Cu corrosion near the open circuit potential. In contrast, ammonia, methylamine, ethylamine, monoethanolamine, diethylamine, diethanolamine, and piperazine all induced Cu corrosion. Corrosion rates correlate with the pK a and steric hindrance of the amines, highlighting key parameters for catalyst–amine codesign. Grand canonical DFT calculations indicate a correlation between the adsorption strength of protonated amines, their pK a , and the extent of Cu corrosion, suggesting that both the surface binding of protonated amines and the lability of their protons play critical roles in corrosion acceleration near open circuit potentials. These finding suggest that amines with high pK a values and weak binding of their protonated forms to Cu surfaces are preferred, as they offer better corrosion resistance.

Choi, Jounghwan [Univ. of California, Los Angeles,↗

Phosphocreatine kinetics at the onset of contractions in skeletal muscle of MM creatine kinase knockout mice

Phosphocreatine (PCr) depletion during isometric twitch stimulation at 5 Hz was measured by (31)P-NMR spectroscopy in gastrocnemius muscles of pentobarbital-anesthetized MM creatine kinase knockout (MMKO) vs. wild-type C57B (WT) mice. PCr depletion after 2 s of stimulation, estimated from the difference between spectra gated to times 200 ms and 140 s after 2-s bursts of contractions, was 2.2 +/- 0.6% of initial PCr in MMKO muscle vs. 9.7 +/- 1.6% in WT muscles (mean +/- SE, n = 7, P < 0.001). Initial PCr/ATP ratio and intracellular pH were not significantly different between groups, and there was no detectable change in intracellular pH or ATP in either group after 2 s. The initial difference in net PCr depletion was maintained during the first minute of continuous 5-Hz stimulation. However, there was no significant difference in the quasi-steady-state PCr level approached after 80 s (MMKO 36.1 +/- 3.5 vs. WT 35.5 +/- 4.4% of initial PCr; n = 5-6). A kinetic model of ATPase, creatine kinase, and adenylate kinase fluxes during stimulation was consistent with the observed PCr depletion in MMKO muscle after 2 s only if ADP-stimulated oxidative phosphorylation was included in the model. Taken together, the results suggest that cytoplasmic ADP more rapidly increases and oxidative phosphorylation is more rapidly activated at the onset of contractions in MMKO compared with WT muscles.

NASA Discipline Cell Biology↗

Axion Perturbations: A General Analytical Treatment

Cosmological data provides us two key constraints on dark matter (DM): it must have a particular abundance, and it must have an adiabatic spectrum of density perturbations in the early universe. Many different cosmological scenarios have been proposed that establish the abundance of axion DM in qualitatively different ways. In this paper we emphasize that, despite this variety of backgrounds, the perturbations in axion DM can be understood from universal principles. How does a feebly interacting axion field acquire perturbations proportional to those of photons? How do the isocurvature power spectrum and non-Gaussianity depend on the background evolution of the universe? We answer these questions for a completely general choice of cosmological background and temperature-dependent axion potential. We show that the most general solution to the axion field equation on super-horizon scales is entirely determined by the family of background solutions for different initial field values . This holds for both the component in the field perturbation solution contributing to the DM isocurvature perturbation (enhanced at late times by the sensitivity of the DM abundance to the initial condition, , which can be large for initial conditions near the hilltop), and the other component that contributes to the DM curvature perturbation. In particular, we explain that an unperturbed axion field in the early universe evolving into one with nontrivial adiabatic perturbations is guaranteed by Weinberg's theorem on adiabatic modes. These results have been derived before with various assumptions, such as a radiation dominated background or a quadratic potential. Our aim is to give a clear, simple derivation that is manifestly independent of those assumptions, and thus can be applied to any cosmological axion scenario.

Cosmology and Nongalactic Astrophysics (astro-ph.C↗

Quantum simulation of massive Thirring and Gross--Neveu models for arbitrary number of flavors

The study of fermionic quantum field theories is an important problem for realizing the standard model of particle physics on a quantum computer. As a step towards this goal, we consider the massive Thirring and Gross--Neveu models with arbitrary number of fermion flavors, $N_f$, discretized on a spatial one-dimensional lattice of size $L$ in the Hamiltonian formulation. We compute the gate complexity using the higher-order product formula and using block-encoding/qubitization and quantum singular value transformations in the limit of large $N_f$ and $L$. We also prepare the ground states of both models with excellent fidelity for system sizes up to 20 qubits with $N_f = 1,2,3,4$ using the adaptive-variational quantum imaginary time algorithm. In addition, we also classify the dynamical Lie algebras of these relativistic fermionic models and show that they belong to the same isomorphism class. Our work is a concrete step towards the quantum simulation of real-time dynamics of large $N_f$ fermionic quantum field theories models relevant for chiral symmetry breaking, understanding dimensional transmutation, and exploring the conformal window of field theories on near-term and early fault-tolerant quantum computers.

FOS: Physical sciences↗

Benchmarking a Tunable Quantum Neural Network on Trapped-Ion and Superconducting Hardware

We implement a quantum generalization of a neural network on trapped-ion and IBM superconducting quantum computers to classify MNIST images, a common benchmark in computer vision. The network feedforward involves qubit rotations whose angles depend on the results of measurements in the previous layer. The network is trained via simulation, but inference is performed experimentally on quantum hardware. The classical-to-quantum correspondence is controlled by an interpolation parameter, $a$, which is zero in the classical limit. Increasing $a$ introduces quantum uncertainty into the measurements, which is shown to improve network performance at moderate values of the interpolation parameter. We then focus on particular images that fail to be classified by a classical neural network but are detected correctly in the quantum network. For such borderline cases, we observe strong deviations from the simulated behavior. We attribute this to physical noise, which causes the output to fluctuate between nearby minima of the classification energy landscape. Such strong sensitivity to physical noise is absent for clear images. We further benchmark physical noise by inserting additional single-qubit and two-qubit gate pairs into the neural network circuits. Our work provides a springboard toward more complex quantum neural networks on current devices: while the approach is rooted in standard classical machine learning, scaling up such networks may prove classically non-simulable and could offer a route to near-term quantum advantage.

FOS: Physical sciences↗

Reaction of YBa2Cu3O(7-beta) with Gold, Silver, Bismuth and Lead: Substitution Chemistry and Composite Fabrication

The reaction of YBa2Cu3O(7-beta) with Au, Ag, Bi, and Ph ions or metal is described. Three types of materials were produced: a well-defined series of homogeneous superconductors was obtained for Au ion substitution with little effect on T(sub c); attempted Ag and Bi ion substitution resulted in multi-phase samples with slightly enhanced T(sub c); finally, attempts to produce superconducting metal/superconducting ceramic composites with Pb and Bi powders resulted in multi-phase samples with drastically diminished superconducting properties. For Au- substituted superconductors, YBa2(Cu(l-x)Au(x))3O(7-beta), a substitution series (x = 0 - 0.1) has been synthesized. For x = 0.1 there was no change in the a and b lattice parameters (a = 3.826 A and b = 3.889 A) but a 0.06 A c axis expansion to 11.75 A was observed. The valence of Cu and Au in YBa2Au(0.3)Cu(2.7)O(7-beta) was investigated using X-ray Absorption Near-Edge Structure (XANES). X-ray studies indicate that Au goes into the Cu(l) site and Cu K edge XANES shows that this has little effect on the oxidation state of the remaining copper. A small effect on T(sub c) is observed (T(sub c) = 89 K for x = 0.10). Ag and Bi addition results in a rise in T(sub c) and a decrease in (delta)T(sub c) at low levels (x = 0.10 Ag, T(sub c) = 94 K and (delta)T(sub c) = 0.5 K; x = 0.02 Bi, T(sub c) = 94 K and (delta)T(sub c) = 1K) relative to typical values for YBa2Cu3O(7-beta) (T(sub c) = 91 K, (delta)T(sub c) = 2 K). Attempts at fabrication of Pb- and Pb(1-x)Bi(x)-superconductor composites are described. Cold pressing followed by low temperature (200 C) sintering resulted in a composite which excluded flux below 90 K but did not show zero electrical resistance until the metal (alloy) superconducting transition. X-ray diffraction showed the presence of pervoskite and metal. Processing at moderate (450 C) or high (950 C) temperatures resulted in oxygen-depleted pervoskite and/or metal oxides. These materials displayed greatly degraded superconducting properties. Processing at 800 C resulted in high T(sub c) only for composites containing greater than 90% weight fraction ceramic. Reaction of metal with YBa2Cu3O(7-beta) formed superconducting lead/bismuth-based oxides and other binary oxides.

Hepp, Aloysius F.↗

Wino and Real Minimal Dark Matter Excluded by Fermi Gamma-Ray Observations

We show that minimal, fermionic dark matter (DM) models in the $n$-dimensional representation of the weak force with zero hypercharge that make up 100% of the DM under the standard cosmological history are strongly excluded for $n < 9$. This includes the thermal wino, which we show is ruled out even allowing for DM core sizes up to $\sim$6.7 kpc with the preferred local DM density or $\sim$3.7 kpc in addition to the local DM density being half the preferred value, at less than $0.2$ GeV/cm$^3$. We reach these conclusions through dedicated searches with 14 years of Fermi gamma-ray data in the inner Galaxy between 30 GeV and 2 TeV for the continuum gamma-rays produced in the decays of unstable particles produced in DM annihilation and bound-state formation processes. We consider a variety of Milky Way DM profiles in our analyses, including those motivated by modern hydrodynamic cosmological simulations, and show that all the $n < 9$ minimal DM models are disfavored even under the most conservative assumptions for these density profiles. While wino, quintuplet ($n=5$), and $n = 7$ DM models are strongly disfavored by our analyses under the standard cosmology, we discuss how non-standard cosmological histories or DM sub-fractions could still allow for these particles to be realized in nature, with discovery opportunities at next-generation particle colliders and gamma-ray telescopes.

Cosmology and Nongalactic Astrophysics (astro-ph.C↗

Coincident learning for beam-based rf station fault identification using phase information at the SLAC linac coherent light source

Anomalies in radio-frequency (rf) stations can result in unplanned downtime and performance degradation in linear accelerators such as SLAC’s Linac Coherent Light Source (LCLS). Detecting these anomalies is challenging due to the complexity of accelerator systems, high data volume, and scarcity of labeled fault data. Prior work identified faults using beam-based detection, combining rf amplitude and beam position monitor data. Due to the simplicity of the rf amplitude data, classical methods are sufficient to identify faults, but the recall is constrained by the low-frequency and asynchronous characteristics of the data. In this work, we leverage high-frequency, time-synchronous rf phase data to enhance anomaly detection in the LCLS accelerator. Due to the complexity of phase data, classical methods fail, and we instead train deep neural networks within the Coincident Anomaly Detection (CoAD) framework. We find that applying CoAD to phase data detects nearly 3 times as many anomalies as when applied to amplitude data, while achieving broader coverage across rf stations. Furthermore, the rich structure of phase data enables us to cluster anomalies into distinct physical categories. Through the integration of auxiliary system status bits, we link clusters to specific fault signatures, providing additional granularity for uncovering the root cause of faults. We also investigate interpretability via Shapley values, confirming that the learned models focus on the most informative regions of the data and providing insight for cases where the model makes mistakes. This work demonstrates that phase-based anomaly detection for rf stations improves both diagnostic coverage and root cause analysis in accelerator systems and that deep neural networks are essential for effective analysis.

Accelerator Physics (physics.acc-ph)↗

A data base of crop nutrient use, water use, and carbon dioxide exchange in a 2O square meter growth chamber: I. Wheat as a case study

A data set is given describing the daily nutrient uptake, gas exchange, environmental conditions, and carbon (C), and nutrient partitioning at harvest for the entire canopy and root system of a wheat crop (Triticum aestivum, cv. Yecora Rojo). The data were obtained from a 20 m2 stand of wheat plants grown from planting to maturity in a closed, controlled environment, and include daily nutrient uptake [macronutrients, nitrogen (N), phosphorus (P), potassium (K), calcium (Ca), magnesium (Mg), and sulfur (S); and micronutrients, iron (Fe), boron (B), manganese (Mn), zinc (Zn), copper (Cu), and molybdenum (Mo)], canopy carbon dioxide (CO2) exchange rates, and transpiration. Environmental factors such as relative humidity, air temperature, nutrient solution temperature, pH and electrical conductivity, and photoperiod were controlled in the chamber to specific set points. A detailed description of biomass yield for each of the 64 plant growth trays comprising the 20 m2 of growth area is also provided, and includes dry weights of grain, straw, chaff, and roots, along with the concentration of nutrients in different plant tissues and the percent carbohydrate, fat, and protein. To our knowledge, this information represents one of the most extensive data sets available for a canopy of wheat grown from seed to maturity under controlled environmental and nutritional conditions, and thus may provide useful information for model development and validation. A methods section is included to qualify any assumptions that might be required for the use of the data in plant growth models, along with a daily event calendar indicating when adjustments in set points and occasional equipment or sensor failures occurred.

NASA Discipline Number 61-20↗

Aerosol Seasonal Variations over Urban-Industrial Regions in Ukraine According to AERONET and POLDER Measurements

The paper presents an investigation of aerosol seasonal variations in several urban-industrial regions in Ukraine. Our analysis of seasonal variations of optical and physical aerosol parameters is based on the sun-photometer 2008-2013 data from two urban ground-based AERONET (AErosol RObotic NETwork) sites in Ukraine (Kyiv, Lugansk) as well as on satellite POLDER instrument data for urban-industrial areas in Ukraine. We also analyzed the data from one AERONET site in Belarus (Minsk) in order to compare with the Ukrainian sites. Aerosol amount and optical depth (AOD) values in the atmosphere columns over the large urbanized areas like Kyiv and Minsk have maximum values in the spring (April-May) and late summer (August), whereas minimum values are observed in late autumn. The results show that fine-mode particles are most frequently detected during the spring and late summer seasons. The analysis of the seasonal AOD variations over the urban-industrial areas in the eastern and central parts of Ukraine according to both ground-based and POLDER data exhibits the similar traits. The seasonal variation similarity in the regions denotes the resemblance in basic aerosol sources that are closely related to properties of aerosol particles. The behavior of basic aerosol parameters in the western part of Ukraine is different from eastern and central regions and shows an earlier appearance of the spring and summer AOD maxima. Spectral single-scattering albedo, complex refractive index and size distribution of aerosol particles in the atmosphere column over Kyiv have different behavior for warm (April-October) and cold seasons. The seasonal features of fine and coarse aerosol particle behavior over the Kyiv site were analyzed. A prevailing influence of the fine-mode particles on the optical properties of the aerosol layer over the region has been established. The back-trajectory and cluster analysis techniques were applied to study the seasonal back trajectories and prevailing directions of the arrived air mass for the Kyiv and Minsk sites.

Ukraine↗