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Quartz crystals with zircon inclusions were synthesized using a piston-cylinder apparatus to experimentally evaluate the use of inclusions in “soft” host minerals for elastic thermobarometry. Synthesized zircon inclusion strains and, therefore, pressures (P_inc) were measured using Raman spectroscopy and then compared with the expected inclusion strains and pressures calculated from elastic models. Measured inclusion strains and inclusion pressures are systematically more tensile than the expected values and, thus, re-calculated entrapment pressures are overestimated. These discrepancies are not caused by analytical biases or assumptions in the elastic models and strain calculations. Analysis shows that inclusion strain discrepancies progressively decrease with decreasing experimental temperature in the α-quartz field. This behavior is consistent with inelastic deformation of the host–inclusion pairs induced by the development of large differential stresses during experimental cooling. Therefore, inclusion strains are more reliable for inclusions trapped at lower temperature conditions in the α-quartz field where there is less inelastic deformation of the host–inclusion systems. On the other hand, entrapment isomekes of zircon inclusions entrapped in the β-quartz stability field plot along the α–β quartz phase boundary, suggesting that the inclusion strains were mechanically reset at the phase boundary during experimental cooling and decompression. Therefore, inclusions contained in soft host minerals can be used for elastic thermobarometry and inclusions contained in β-quartz may provide constraints on theP–Tat which the host–inclusion system crossed the phase boundary during exhumation.

 

Powered knee-ankle prostheses can offer benefits over conventional passive devices during stair locomotion by providing biomimetic net-positive work and active control of joint angles. However, many modern control approaches for stair ascent and descent are often limited by time-consuming hand-tuning of user/task-specific parameters, predefined trajectories that remove user volition, or heuristic approaches that cannot be applied to both stair ascent and descent. This work presents a phase-based hybrid kinematic and impedance controller (HKIC) that allows for semi-volitional, biomimetic stair ascent and descent at a variety of step heights. We define a unified phase variable for both stair ascent and descent that utilizes lower-limb geometry to adjust to different users and step heights. We extend our prior data-driven impedance model for variable-incline walking, modifying the cost function and constraints to create a continuously-varying impedance parameter model for stair ascent and descent over a continuum of step heights. Experiments with above-knee amputee participants (N=2) validate that our HKIC controller produces biomimetic ascent and descent joint kinematics, kinetics, and work across four step height configurations. We also show improved kinematic performance with our HKIC controller in comparison to a passive microprocessor-controlled device during stair locomotion. 

Supported by considerable public investment through post-9/11 higher education benefits, student military service members/veterans (SSM/Vs) have been one of the fastest-growing groups of nontraditional students in American universities in recent years. Despite their increased numbers and potential to diversify science, technology, engineering, mathematics, and medical (STEMM) fields, little research has explored SSM/V academic development and success across university STEMM contexts. This mixed methods study used social capital theory to explore links between STEMM SSM/V social support and a sense of campus belonging—shown to be important to achievement among traditionally marginalized college students—within 4-year campus communities. Social network analyses of surveys indicated that larger SSM/V support networks, including on- and off-campus social ties as well as student and university educator ties, positively correlated with campus belonging. Social support networks with military ties, traditionally seen to benefit SSM/V college integration, did not correlate. Interview responses suggested that while belonging can be discouraged among SSM/Vs by military-associated STEMM imposter feelings, it is fostered through student friendship, faculty care, and veteran-focused campus support. Results underscored the importance of authentic interaction as well as purposeful efforts to bring SSM/Vs together with fellow students, educators, and staff. 

The millisecond pulsar J1713+0747 underwent a sudden and significant pulse shape change between 2021 April 16 and 17 (MJDs 59320 and 59321). Subsequently, the pulse shape gradually recovered over the course of several months. We report the results of continued multifrequency radio observations of the pulsar made using the Canadian Hydrogen Intensity Mapping Experiment and the 100 m Green Bank Telescope in a 3 yr period encompassing the shape change event, between 2020 February and 2023 February. As of 2023 February, the pulse shape had returned to a state similar to that seen before the event, but with measurable changes remaining. The amplitude of the shape change and the accompanying time-of-arrival residuals display a strong nonmonotonic dependence on radio frequency, demonstrating that the event is neither a glitch (the effects of which should be independent of radio frequency,ν) nor a change in dispersion measure alone (which would produce a delay proportional toν⁻²). However, it does bear some resemblance to the two previous “chromatic timing events” observed in J1713+0747, as well as to a similar event observed in PSR J1643−1224 in 2015.

 

Classroom environments are challenging for artificially intelligent agents primarily because classroom noise dilutes the interpretability and usefulness of gathered data. This problem is exacerbated when groups of students participate in collaborative problem solving (CPS). Here, we examine how well six popular microphones capture audio from individual groups. A primary usage of audio data is automatic speech recognition (ASR), therefore we evaluate our recordings by examining the accuracy of downstream ASR using the Google Cloud Platform. We simultaneously captured the audio of all microphones for 11 unique groups of three participants first reading a prepared script, and then participating in a collaborative problem solving exercise. We vary participants, noise conditions, and speech contexts. Transcribed speech was evaluated using word error rate (WER). We find that scripted speech is transcribed with a surprisingly high degree of accuracy across groups (average WER = 0.114, SD = 0.044). However, the CPS task was much more difficult (average WER = 0.570, SD = 0.143). We found most microphones were robust to background noise below a certain threshold, but the AT-Cardioid and ProCon microphones were more robust to higher noise levels. Finally, an analysis of errors revealed that most errors were due to the ASR missing words/phrases, rather than mistranscribing them. We conclude with recommendations based on our observations. 

Recently we found compelling evidence for a gravitational-wave background with Hellings and Downs (HD) correlations in our 15 yr data set. These correlations describe gravitational waves as predicted by general relativity, which has two transverse polarization modes. However, more general metric theories of gravity can have additional polarization modes, which produce different interpulsar correlations. In this work, we search the NANOGrav 15 yr data set for evidence of a gravitational-wave background with quadrupolar HD and scalar-transverse (ST) correlations. We find that HD correlations are the best fit to the data and no significant evidence in favor of ST correlations. While Bayes factors show strong evidence for a correlated signal, the data does not strongly prefer either correlation signature, with Bayes factors ∼2 when comparing HD to ST correlations, and ∼1 for HD plus ST correlations to HD correlations alone. However, when modeled alongside HD correlations, the amplitude and spectral index posteriors for ST correlations are uninformative, with the HD process accounting for the vast majority of the total signal. Using the optimal statistic, a frequentist technique that focuses on the pulsar-pair cross-correlations, we find median signal-to-noise ratios of 5.0 for HD and 4.6 for ST correlations when fit for separately, and median signal-to-noise ratios of 3.5 for HD and 3.0 for ST correlations when fit for simultaneously. While the signal-to-noise ratios for each of the correlations are comparable, the estimated amplitude and spectral index for HD are a significantly better fit to the total signal, in agreement with our Bayesian analysis.

 

The radio galaxy 3C 66B has been hypothesized to host a supermassive black hole binary (SMBHB) at its center based on electromagnetic observations. Its apparent 1.05 yr period and low redshift (∼0.02) make it an interesting testbed to search for low-frequency gravitational waves (GWs) using pulsar timing array (PTA) experiments. This source has been subjected to multiple searches for continuous GWs from a circular SMBHB, resulting in progressively more stringent constraints on its GW amplitude and chirp mass. In this paper, we develop a pipeline for performing Bayesian targeted searches for eccentric SMBHBs in PTA data sets, and test its efficacy by applying it to simulated data sets with varying injected signal strengths. We also search for a realistic eccentric SMBHB source in 3C 66B using the NANOGrav 12.5 yr data set employing PTA signal models containing Earth term-only as well as Earth+pulsar term contributions using this pipeline. Due to limitations in our PTA signal model, we get meaningful results only when the initial eccentricitye₀< 0.5 and the symmetric mass ratioη> 0.1. We find no evidence for an eccentric SMBHB signal in our data, and therefore place 95% upper limits on the PTA signal amplitude of 88.1 ± 3.7 ns for the Earth term-only and 81.74 ± 0.86 ns for the Earth+pulsar term searches fore₀< 0.5 andη> 0.1. Similar 95% upper limits on the chirp mass are (1.98 ± 0.05) × 10⁹and (1.81 ± 0.01) × 10⁹M_☉. These upper limits, while less stringent than those calculated from a circular binary search in the NANOGrav 12.5 yr data set, are consistent with the SMBHB model of 3C 66B developed from electromagnetic observations.

 

It has recently been demonstrated experimentally that a turbulent plasma created by the collision of two inhomogeneous, asymmetric, weakly magnetized, laser-produced plasma jets can generate strong stochastic magnetic fields via the small-scale turbulent dynamo mechanism, provided the magnetic Reynolds number of the plasma is sufficiently large. In this paper, we compare such a plasma with one arising from two pre-magnetized plasma jets whose creation is identical save for the addition of a strong external magnetic field imposed by a pulsed magnetic field generator. We investigate the differences between the two turbulent systems using a Thomson-scattering diagnostic, x-ray self-emission imaging, and proton radiography. The Thomson-scattering spectra and x-ray images suggest that the external magnetic field has a limited effect on the plasma dynamics in the experiment. Although the external magnetic field induces collimation of the flows in the colliding plasma jets and although the initial strengths of the magnetic fields arising from the interaction between the colliding jets are significantly larger as a result of the external field, the energies and morphologies of the stochastic magnetic fields post-amplification are indistinguishable. We conclude that, for turbulent laser-plasmas with supercritical magnetic Reynolds numbers, the dynamo-amplified magnetic fields are determined by the turbulent dynamics rather than the seed fields or modest changes in the initial flow dynamics of the plasma, a finding consistent with theoretical expectations and simulations of turbulent dynamos. 

Analyses of pulsar timing data have provided evidence for a stochastic gravitational wave background in the nanohertz frequency band. The most plausible source of this background is the superposition of signals from millions of supermassive black hole binaries. The standard statistical techniques used to search for this background and assess its significance make several simplifying assumptions, namely (i) Gaussianity, (ii) isotropy, and most often, (iii) a power-law spectrum. However, a stochastic background from a finite collection of binaries does not exactly satisfy any of these assumptions. To understand the effect of these assumptions, we test standard analysis techniques on a large collection of realistic simulated data sets. The data-set length, observing schedule, and noise levels were chosen to emulate the NANOGrav 15 yr data set. Simulated signals from millions of binaries drawn from models based on the Illustris cosmological hydrodynamical simulation were added to the data. We find that the standard statistical methods perform remarkably well on these simulated data sets, even though their fundamental assumptions are not strictly met. They are able to achieve a confident detection of the background. However, even for a fixed set of astrophysical parameters, different realizations of the universe result in a large variance in the significance and recovered parameters of the background. We also find that the presence of loud individual binaries can bias the spectral recovery of the background if we do not account for them.