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At least 991 records · Page 55

Critical behavior in monoclinic Cr 3 ⁢Te 4

High-quality monoclinic Cr 3 ⁢Te 4 crystals are synthesized by the chemical vapor transport method and confirmed by synchrotron powder x-ray diffraction. Critical behaviors of Cr 3 ⁢Te 4 are studied by bulk isothermal magnetization measurements around its paramagnetic to ferromagnetic phase transition. From these data, we evaluate the modified Arrott plot, the Kouvel-Fisher plot, and critical isotherms, and estimate critical exponent values of β~0.3827, γ~1.2119, and δ~4.16, and the Curie temperature T C ≈321 K. After the scaling, the isothermal magnetization curves below and above the critical temperatures collapse into two independent universal branches which signifies the reliability of our critical exponent estimation. Finally, the estimated critical exponent values of Cr 3 ⁢Te 4 do not match well with theoretically calculated values of any three-dimensional models.

36 MATERIALS SCIENCE↗

Net-proton fluctuations influenced by baryon stopping and quark deconfinement

Preliminary data from the Beam-Energy Scan II measurements by the STAR Collaboration at the Relativistic Heavy Ion Collider suggest a dip in the fourth-to-second-order cumulant ratio when plotted vs beam energy. At the same energy range where the structure appears, a transition from hadrons to quarks is expected, the deconfinement transition. In this paper, the role of quark deconfinement in establishing fluctuations in the early stages of the collision is considered. Two models are compared: one with stopping occurring on a baryon-by-baryon basis, and a second where stopping proceeds through quark degrees of freedom. In the latter model, the fluctuation of baryon number is significantly reduced and this signal is found to survive recombination into hadrons and the subsequent diffusion. The transformation from baryon to quark stopping thus produces a dip in the fourth-to-second-order cumulant ratio when plotted vs beam energy, consistent with observations.

Baryons↗

Precise absolute γ -ray and β - -decay branching intensities in the decay of Cu 29 67

In this work, absolute γ-ray emission probabilities in the β - decay of 67 Cu were measured by means of γ-ray and β - -decay singles and β - -γ coincidences. The new results, together with the known decay scheme of 67 Cu , were used to determine absolute β - -decay branching intensities. The present data differ significantly from previously published values. In addition, the half-life of the I π = 1/2 - isomer in 67 Zn was measured as T 1/2 = 9.37(4) μs, in a good agreement with earlier measurements. Lastly, from the analysis of the Fermi–Kurie plots, Q β - ( g.s.) = 560.3 (10) keV was deduced, which differs from the previously measured value of 577(8) keV but is in good agreement with Q β - ( g.s.) = 561.3 (15) keV recommended in the latest Atomic Mass Evaluation.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Revealing Fine Structure in the Antineutrino Spectra from a Nuclear Reactor

Here, we calculate the Inverse Beta Decay (IBD) antineutrino spectrum generated by nuclear reactors using the summation method to understand deviations from the smooth Huber-Mueller model due to the decay of individual fission products, showing that plotting the ratio of two adjacent spectra points can effectively reveal these deviations. We obtain that for binning energies of 0.1 MeV or lower, abrupt changes in the spectra due to the jagged nature of the individual antineutrino spectra could be observed for highly precise experiments. Surprisingly, our calculations also reveal a peak-like feature in the adjacent points ratio plot at 4.5 MeV even with a 0.25 MeV binning interval, which we find is present in the IBD spectrum published by Daya Bay in 2016. We show that this 4.5 MeV feature is caused by the contributions of just four fission products, 95 Y, 98,101 Nb and 102 T c . This would be the first evidence of the decay of a few fission products in the IBD antineutrino spectrum from a nuclear reactor. This result is supported by applying the same numerical technique to measured aggregate electron spectra.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Dalitz analysis of $D^0 → K^–π^+η$ decays at Belle

We present the results of the first Dalitz plot analysis of the decay D 0 → K – π + η . The analysis is performed on a data set corresponding to an integrated luminosity of 953 fb – 1 collected by the Belle detector at the asymmetric-energy e + e – KEKB collider. The Dalitz plot is well described by a combination of the six resonant decay channels K ¯ * ( 892 ) 0 η , K – a 0 ( 980 ) + , K – a 2 ( 1320 ) + , K ¯ * ( 1410 ) 0 η , K * ( 1680 ) – π + and K 2 * ( 1980 ) – π + , together with K π and K η S-wave components. The decays K * ( 1680 ) – → K – η and K 2 * ( 1980 ) – → K – η are observed for the first time. We measure ratio of the branching fractions, B ( D 0 → K – π + η ) B ( D 0 → K – π + ) = 0.500 ± 0.002 ( stat ) ± 0.020 ( syst ) ± 0.003 ( B PDG ) . Using the Dalitz fit result, the ratio B ( K * ( 1680 ) → K η ) B ( K * ( 1680 ) → K π ) is measured to be 0.11 ± 0.02 ( stat ) – 0.04 + 0.06 ( syst ) ± 0.04 ( B PDG ) ; this is much lower than the theoretical expectations ( ≈ 1 ) made under the assumption that K * ( 1680 ) is a pure 1 3 D 1 state. The product branching fraction B ( D 0 → [ K 2 * ( 1980 ) – → K – η ] π + ) = ( 2. 2 – 1.9 + 1.7 ) × 10 – 4 is determined. In addition, the π η ' contribution to the a 0 ( 980 ) ± resonance shape is confirmed with 10.1 σ statistical significance using the three-channel Flatté model. We also measure B ( D 0 → K ¯ * ( 892 ) 0 η ) = ( 1.4 1 – 0.12 + 0.13 ) % . This is consistent with, and more precise than, the current world average ( 1.02 ± 0.30 ) % , deviates with a significance of more than 3 σ from the theoretical predictions of (0.51–0.92)%.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Dijet and electroweak limits on a Z ′ boson coupled to quarks

An insightful way of presenting the LHC limits on dijet resonances is the coupling-mass plot for a Z ′ boson that has flavor-independent quark interactions. This also illustrates the comparison of low-mass LHC sensitivity with constraints on the flavor-independent Z ′ boson from electroweak and quarkonium measurements. To derive these constraints, we compute the Z ′ mixing with the Z , the photon, and the ϒ meson, emphasizing the logarithmic dependence on the masses of the new electroweak-charged fermions (“anomalons”) required to cancel the gauge anomalies. We update the coupling-mass plot, extending it for Z ′ masses from 5 GeV to 5 TeV. Published by the American Physical Society 2024

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Classification of AB O 3 perovskite solids: a machine learning study

Here we explored the use of machine learning methods for classifying whether a particular AB O 3 chemistry forms a perovskite or non-perovskite structured solid. Starting with three sets of feature pairs (the tolerance and octahedral factors, the A and B ionic radii relative to the radius of O, and the bond valence distances between the A and B ions from the O atoms), we used machine learning to create a hyper-dimensional partial dependency structure plot using all three feature pairs or any two of them. Doing so increased the accuracy of our predictions by 2–3 percentage points over using any one pair. We also included the Mendeleev numbers of the A and B atoms to this set of feature pairs. Moreover, doing this and using the capabilities of our machine learning algorithm, the gradient tree boosting classifier, enabled us to generate a new type of structure plot that has the simplicity of one based on using just the Mendeleev numbers, but with the added advantages of having a higher accuracy and providing a measure of likelihood of the predicted structure.

36 MATERIALS SCIENCE↗

Overall protein structure quality assessment using hydrogen-bonding parameters

Atomic model refinement at low resolution is often a challenging task. This is mostly because the experimental data are not sufficiently detailed to be described by atomic models. To make refinement practical and ensure that a refined atomic model is geometrically meaningful, additional information needs to be used such as restraints on Ramachandran plot distributions or residue side-chain rotameric states. However, using Ramachandran plots or rotameric states as refinement targets diminishes the validating power of these tools. Therefore, finding additional model-validation criteria that are not used or are difficult to use as refinement goals is desirable. Hydrogen bonds are one of the important noncovalent interactions that shape and maintain protein structure. These interactions can be characterized by a specific geometry of hydrogen donor and acceptor atoms. Systematic analysis of these geometries performed for quality-filtered high-resolution models of proteins from the Protein Data Bank shows that they have a distinct and a conserved distribution. Here, it is demonstrated how this information can be used for atomic model validation.

59 BASIC BIOLOGICAL SCIENCES↗

Transformer Leakage Inductance Design Methodology

The leakage inductance exhibited by a transformer depends on its winding geometry, which generally involves the selection of several key design parameters in addition to the winding structure and the interleaving configuration. With few resources explaining the effects of these design choices on the observed leakage inductance, numerous trial-and-error iterations become necessary to realize the desired leakage inductance. This paper explores more than a hundred winding geometries feasible in a 2-winding transformer comprising the same magnetic core, number of turns, and wire gauge, and finds the leakage inductance for each unique design using 2-D finite element method (FEM) simulations in association with the semi-analytical double- 2-D model. These leakage inductances are plotted and further analyzed to understand the effects of different design parameters on the effective leakage inductance. The results presented herein and the conclusions drawn from this research can serve as a valuable resource for future design practitioners from both industry and academia.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Thermal Management System for an Electric Machine with Additively Manufactured Hollow Conductors with Integrated Heat Pipes: Preprint

This paper discusses steps taken to size a thermal management system for an aircraft propulsion electric machine containing additively manufactured coils integrated with heat pipes aimed at boosting its specific power. Experimental setups are used to size and characterize heat pipes for the application and 3D thermal FEA is used to determine optimum heat transfer coefficient of convective boundaries. Geometric details of fin-based surface area enhancement required to reach target combined overall heat transfer coefficient (U) and surface area (A) performance (UA) in W/K, is worked out for relevant boundaries and the resulting UA is verified in 3D thermal FEA. Thermal management system's UA (by extension specific power) sensitivity to coolant temperature is explored and temperature distribution plots of optimized machine components are presented and discussed.

additive manufacturing↗

Visualization of Noisy and Less Noisy Computational Basis States in Quantum Computing

Quantum computing technology holds substantial promise as a reliable computational paradigm. However, current noisy intermediate scale quantum (NISQ) systems, are significantly impacted by noise originating from hardware inconsistencies. This noise causes errors and lowers output fidelity. So we must find which basis states cause errors. However, there are two main challenges in analyzing noise corresponding to basis states. First, the noise distribution data is high dimensional in nature, thereby making its analysis challenging. Second, although functional box plots have been used in the state of the art research to understand such a high dimensional data, they suffer from clutter and occlusion issues because of overplotting. In this study, we introduce an innovative visualization pipeline to address the aforementioned challenges to provide a clear depiction of noisy and less-noisy basis states. Specifically, our proposed visualization pipeline comprises three stages namely, low dimensional embedding, clustering, and violin plot visualization, to reduce visual clutter and effectively analyze high-dimensional noise distribution data. Our analysis uses quantum machine learning (QML) circuits as case study for drawing a distinction between noisy and less noisy basis states.

Senapati, Priyabrata [Kent State University]↗

Field Quality and Fabrication Analysis of HQ02 Reconstructed Nb3Sn Coil Cross Sections

© 2017 IEEE. The U.S. LHC Accelerator Research Program (LARP) quadrupole HQ02 was designed and fully tested as part of the low-beta quad development for Hi-Lumi LHC. HQ02's design is well documented with full fabrication accounting along with full field analysis at low and high current. With this history, HQ02 is an excellent test bed for developing a methodology for measuring turn locations from magnet cross sections and comparing with CAD models and measured field. All four coils of HQ02 were cut in identical locations along the magnetic length corresponding to magnetic field measurement and coil metrology. A real-time camera and coordinate measuring equipment was used to plot turn corners. Measurements include systematic and random displacements of winding blocks and individual turns along the magnetic length. The range of cable shifts and the field harmonic range along the length are in agreement, although correlating turn locations and measured harmonics in each cross section is challenging.

Holik, Eddie Frank↗

Scalable Comparative Visualization of Ensembles of Call Graphs

Optimizing the performance of large-scale parallel codes is critical for efficient utilization of computing resources. Code developers often explore various execution parameters, such as hardware configurations, system software choices, and application parameters, and are interested in detecting and understanding bottlenecks in different executions. They often collect hierarchical performance profiles represented as call graphs, which combine performance metrics with their execution contexts. The crucial task of exploring multiple call graphs together is tedious and challenging because of the many structural differences in the execution contexts and significant variability in the collected performance metrics (e.g., execution runtime). In this paper, we present Ensemble CallFlow to support the exploration of ensembles of call graphs using new types of visualizations, analysis, graph operations, and features. We introduce ensemble-Sankey , a new visual design that combines the strengths of resource-flow (Sankey) and box-plot visualization techniques. Whereas the resource-flow visualization can easily and intuitively describe the graphical nature of the call graph, the box plots overlaid on the nodes of Sankey convey the performance variability within the ensemble. Our interactive visual interface provides linked views to help explore ensembles of call graphs, e.g., by facilitating the analysis of structural differences, and identifying similar or distinct call graphs. Finally, we demonstrate the effectiveness and usefulness of our design through case studies on large-scale parallel codes.

97 MATHEMATICS AND COMPUTING↗

Nest survival modelling using a multi‐species approach in forests managed for timber and biofuel feedstock

Abstract Switchgrass ( Panicum virgatum ) intercropping is a novel forest management practice for biomass production intended to generate cellulosic feedstocks within intensively managed loblolly pine‐dominated landscapes. These pine plantations are important for early‐successional bird species, as short rotation times continually maintain early‐successional habitat. We tested the efficacy of using community models compared to individual surrogate species models in understanding influences on nest survival. We analysed nest data to test for differences in habitat use for 14 bird species in plots managed for switchgrass intercropping and controls within loblolly pine ( Pinus taeda ) plantations in Mississippi, USA. We adapted hierarchical models using hyper‐parameters to incorporate information from both common and rare species to understand community‐level nest survival. This approach incorporates rare species that are often discarded due to low sample sizes, but can inform community‐level demographic parameter estimates. We illustrate use of this approach in generating both species‐level and community‐wide estimates of daily survival rates for songbird nests. We were able to include rare species with low sample size (minimum n = 5) to inform a hyper‐prior, allowing us to estimate effects of covariates on daily survival at the community level, then compare this with a single‐species approach using surrogate species. Using single‐species models, we were unable to generate estimates below a sample size of 21 nests per species. Community model species‐level survival and parameter estimates were similar to those generated by five single‐species models, with improved precision in community model parameters. Covariates of nest placement indicated that switchgrass at the nest site (<4 m) reduced daily nest survival, although intercropping at the forest stand level increased daily nest survival. Synthesis and applications . Community models represent a viable method for estimating community nest survival rates and effects of covariates while incorporating limited data for rarely detected species. Intercropping switchgrass in loblolly pine plantations slightly increased daily nest survival at the research plot scale (0.1 km 2 ), although at a local scale (50 m 2 ) switchgrass negatively influenced nest survival. A likely explanation is intercropping shifted community composition, favouring species with greater disturbance tolerance.

Loman, Zachary G.↗

Growth strategies and threshold responses to water deficit modulate effects of warming on tree seedlings from forest to alpine

Predictions of upslope range shifts for tree species with warming are based on assumptions of moisture stress at lower elevation limits and low-temperature stress at high-elevation limits. However, recent studies have shown that warming can reduce tree seedling establishment across the entire gradient from subalpine forest to alpine via moisture limitation. Warming effects also vary with species, potentially resulting in community shifts in high-elevation forests. We examined the growth and physiology underlying effects of warming on seedling demographic patterns. We evaluated dry mass (DM), root length, allocation above- and below-ground, and relative growth rate (RGR) of whole seedlings, and their ability to avoid or endure water stress via water-use efficiency and resisting turgor loss, for Pinus flexilis , Picea engelmannii and Pinus contorta seeded below, at and above tree line in experimentally warmed, watered and control plots in the Rocky Mountains, USA. We expected that growth and allocation responses to warming would relate to moisture status and that variation in drought tolerance traits would explain species differences in survival rates. Across treatments and elevations, seedlings of all species had weak turgor-loss resistance, and growth was marginal with negative RGR in the first growth phase (-0.01 to -0.04 g g -1 day -1 ). Growth was correlated with soil moisture, particularly in the relatively small-seeded P. contorta and P. engelmannii . Pinus flexilis , known to have the highest survivorship, attained the greatest DM and longest root but was also the slowest growing and most water-use efficient. This was likely due to its greater reliance on seed reserves. Seedlings developed 15% less total DM, 25% less root DM and 11% shorter roots in heated compared with unheated plots. Higher temperatures slightly increased DM, root length and RGR where soils were wettest, but more strongly decreased these variables under drier conditions. Synthesis. The surprising heat inhibition of tree seedling establishment at the cold edge of forests appears to have a physiological basis: newly germinated seedlings have poor moisture stress tolerance, which appears related to marginal initial growth and heavy reliance on seed reserves. Variation in these attributes among tree species at tree line helps explain their different climate responses.

54 ENVIRONMENTAL SCIENCES↗

Climate, soil mineralogy and mycorrhizal fungi influence soil organic matter fractions in eastern US temperate forests

Identifying the primary controls of particulate (POM) and mineral-associated organic matter (MAOM) content in soils is critical for determining future stocks of soil carbon (C) and nitrogen (N) across the globe. However, drivers of these soil organic matter fractions are likely to vary among ecosystems in response to climate, soil type and the composition of local biological communities. We tested how soil factors, climate and plant–fungal associations influenced the distribution and concentrations of C and N in MAOM and POM in seven temperate forests in the National Ecological Observatory Network (NEON) across the eastern United States. Samples of upper mineral horizon soil within each forest were collected in plots representing a gradient of dominant tree–mycorrhizal association, allowing us to test how plant and microbial communities influenced POM and MAOM across sites differing in climate and soil conditions. We found that concentrations of C and N in soil organic matter were primarily driven by soil mineralogy, but the relative abundance of MAOM versus POM C was strongly linked to plot-level mycorrhizal dominance. Furthermore, the effect of dominant tree mycorrhizal type on the distribution of N among POM and MAOM fractions was sensitive to local climate: in cooler sites, an increasing proportion of ectomycorrhizal-associated trees was associated with lower proportions of N in MAOM, but in warmer sites, we found the reverse. As an indicator of soil carbon age, we measured radiocarbon in the MAOM fraction but found that within and across sites, Δ 14 C was unrelated to mycorrhizal dominance, climate, or soil factors, suggesting that additional site-specific factors may be primary determinants of long-term SOM persistence. Our results indicate that while soil mineralogy primarily controls SOM C and N concentrations, the distribution of SOM among density fractions depends on the composition of vegetation and microbial communities, with these effects varying across sites with distinct climates. Here we also suggest that within biomes, the age of mineral-associated soil carbon is not clearly linked to the factors that control concentrations of MAOM C and N.

54 ENVIRONMENTAL SCIENCES↗

Aridity and forest age mediate landscape scale patterns of tropical forest resistance to cyclonic storms

Abstract Cyclonic storms, or hurricanes, are expected to intensify as ocean heat energy rises due to climate change. Ecological theory suggests that tropical forest resistance to hurricanes should increase with forest age and wood density. However, most data on hurricane effects on tropical forests come from a limited number of well‐studied long‐term monitoring sites, restricting our capacity to evaluate the resistance of tropical forests to hurricanes across broad environmental gradients. In this study, we assessed whether forest age and aridity mediate the effects of hurricanes Irma and Maria in Puerto Rico, Vieques and Culebra islands. We leveraged functional trait data for 410 tree species, remotely sensed measurements of canopy height and cover, along with data on forest stand characteristics of 180 of 338 forest monitoring plots, each covering an area of 0.067 ha. The plots represent a broad mean annual precipitation (MAP) gradient from 701 to 4598 mm and a complex mosaic of forest age from 5 to around 85 years since deforestation. Hurricanes resulted in a 25% increase in basal area mortality rates, a 45% decrease in canopy height and a 21% reduction in canopy cover. These effects intensified with forest age, even after considering proximity to the hurricane path. The links between forest age and hurricane disturbances were likely due the prevalence of tall canopies. Tall forest canopies were strongly linked with low community‐weighted wood density (WD). These characteristics were on average more common in moist and wet forests (MAP >1250 mm). Conversely, dry forests were dominated by short species with high wood density (WD > 0.6 g cm −3 ) and did not show significant increases in basal area mortality rates after the hurricanes. Synthesis . Our findings show that selection towards drought‐tolerant traits across aridity gradients, such as short stature and dense wood, enhances resistance to hurricanes. However, forest age modulated responses to hurricanes, with older forests being less resistant across the islands. This evidence highlights the importance of considering the intricate links between ecological succession and plant function when forecasting tropical forests’ responses to increasingly strong hurricanes.

Vargas G., German↗