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  1. Abstract

    In 2019, the Event Horizon Telescope (EHT) released the first-ever image of a black hole event horizon. Astronomers are now aiming for higher angular resolutions of distant targets, like black holes, to understand more about the fundamental laws of gravity that govern our universe. To achieve this higher resolution and increased sensitivity, larger radio telescopes are needed to operate at higher frequencies and in larger quantities. Projects like the next-generation Very Large Array (ngVLA) and the Square-Kilometer Array (SKA) require building hundreds of telescopes with diameters greater than 10 ms over the next decade. This has a twofold effect. Radio telescope surfaces need to be more accurate to operate at higher frequencies, and the logistics involved in maintaining a radio telescope need to be simplified to support them properly in large quantities. Both of these problems can be solved with improved methods for surface metrology that are faster and more accurate with a higher resolution. This leads to faster and more accurate panel alignment and, therefore, a more productive observatory. In this paper, we present the use of binocular fringe projection profilometry as a solution to this problem and demonstrate it by aligning two panels on a 3-m radio telescope dish. The measurement takes only 10 min and directly delivers feedback on the tip, tilt, and piston of each panel to create the ideal reflector shape.

     
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  2. The Standard Performance Evaluation Corporation (SPEC) CPU benchmark has been widely used as a measure of computing performance for decades. The SPEC is an industry-standardized, CPU-intensive benchmark suite and the collective data provide a proxy for the history of worldwide CPU and system performance. Past efforts have not provided or enabled answers to questions such as, how has the SPEC benchmark suite evolved empirically over time and what micro-architecture artifacts have had the most influence on performance? - have any micro-benchmarks within the suite had undue influence on the results and comparisons among the codes? - can the answers to these questions provide insights to the future of computer system performance? To answer these questions, we detail our historical and statistical analysis of specific hardware artifacts (clock frequencies, core counts, etc.) on the performance of the SPEC benchmarks since 1995. We discuss in detail several methods to normalize across benchmark evolutions. We perform both isolated and collective sensitivity analyses for various hardware artifacts and we identify one benchmark (libquantum) that had somewhat undue influence on performance outcomes. We also present the use of SPEC data to predict future performance. 
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    Free, publicly-accessible full text available January 31, 2025
  3. Abstract

    In this work, convolutional neural networks (CNN) are developed to detect and characterize sporadic E (Es), demonstrating an improvement over current methods. This includes a binary classification model to determine ifEsis present, followed by a regression model to estimate theEsordinary mode critical frequency (foEs), a proxy for the intensity, along with the height at which theEslayer occurs (hEs). Signal‐to‐noise ratio (SNR) and excess phase profiles from six Global Navigation Satellite System (GNSS) radio occultation (RO) missions during the years 2008–2022 are used as the inputs of the model. Intensity (foEs) and the height (hEs) values are obtained from the global network of ground‐based Digisonde ionosondes and are used as the “ground truth,” or target variables, during training. After corresponding the two data sets, a total of 36,521 samples are available for training and testing the models. The foEs CNN binary classification model achieved an accuracy of 74% and F1‐score of 0.70. Mean absolute errors (MAE) of 0.63 MHz and 5.81 km along with root‐mean squared errors (RMSE) of 0.95 MHz and 7.89 km were attained for estimating foEs and hEs, respectively, when it was known thatEswas present. When combining the classification and regression models together for use in practical applications where it is unknown ifEsis present, an foEs MAE and RMSE of 0.97 and 1.65 MHz, respectively, were realized. We implemented three other techniques for sporadic E characterization, and found that the CNN model appears to perform better.

     
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    Free, publicly-accessible full text available January 1, 2025
  4. For some intermetallic compounds containing lanthanides, structural transitions can result in intermediate electronic states between trivalency and tetravalency; however, this is rarely observed for praseodymium compounds. The dominant trivalency of praseodymium limits potential discoveries of emergent quantum states in itinerant 4f1systems accessible using Pr4+-based compounds. Here, we use in situ powder x-ray diffraction and in situ electron energy-loss spectroscopy (EELS) to identify an intermetallic example of a dominantly Pr4+state in the polymorphic system Pr2Co3Ge5. The structure-valence transition from a nearly full Pr4+electronic state to a typical Pr3+state shows the potential of Pr-based intermetallic compounds to host valence-unstable states and provides an opportunity to discover previously unknown quantum phenomena. In addition, this work emphasizes the need for complementary techniques like EELS when evaluating the magnetic and electronic properties of Pr intermetallic systems to reveal details easily overlooked when relying on bulk magnetic measurements alone.

     
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    Free, publicly-accessible full text available January 26, 2025
  5. Free, publicly-accessible full text available January 5, 2025
  6. Abstract Introduction

    High-intensity gait training is widely recognized as an effective rehabilitation approach after stroke. Soft robotic exosuits that enhance post-stroke gait mechanics have the potential to improve the rehabilitative outcomes achieved by high-intensity gait training. The objective of thisdevelopment-of-conceptpilot crossover study was to evaluate the outcomes achieved by high-intensity gait training with versus without soft robotic exosuits.

    Methods

    In this 2-arm pilot crossover study, four individuals post-stroke completed twelve visits of speed-based, high-intensity gait training: six consecutive visits of Robotic Exosuit Augmented Locomotion (REAL) gait training and six consecutive visits without the exosuit (CONTROL). The intervention arms were counterbalanced across study participants and separated by 6 + weeks of washout. Walking function was evaluated before and after each intervention using 6-minute walk test (6MWT) distance and 10-m walk test (10mWT) speed. Moreover, 10mWT speeds were evaluated before each training visit, with the time-course of change in walking speed computed for each intervention arm. For each participant, changes in each outcome were compared to minimal clinically-important difference (MCID) thresholds. Secondary analyses focused on changes in propulsion mechanics and associated biomechanical metrics.

    Results

    Large between-group effects were observed for 6MWT distance (d = 1.41) and 10mWT speed (d = 1.14). REAL gait training resulted in an average pre-post change of 68 ± 27 m (p = 0.015) in 6MWT distance, compared to a pre-post change of 30 ± 16 m (p = 0.035) after CONTROL gait training. Similarly, REAL training resulted in a pre-post change of 0.08 ± 0.03 m/s (p = 0.012) in 10mWT speed, compared to a pre-post change of 0.01 ± 06 m/s (p = 0.76) after CONTROL. For both outcomes, 3 of 4 (75%) study participants surpassed MCIDs after REAL training, whereas 1 of 4 (25%) surpassed MCIDs after CONTROL training. Across the training visits, REAL training resulted in a 1.67 faster rate of improvement in walking speed. Similar patterns of improvement were observed for the secondary gait biomechanical outcomes, with REAL training resulting in significantly improved paretic propulsion for 3 of 4 study participants (p < 0.05) compared to 1 of 4 after CONTROL.

    Conclusion

    Soft robotic exosuits have the potential to enhance the rehabilitative outcomes produced by high-intensity gait training after stroke. Findings of thisdevelopment-of-conceptpilot crossover trial motivate continued development and study of the REAL gait training program.

     
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    Free, publicly-accessible full text available December 1, 2024
  7. Abstract Insect wings must be flexible, light, and strong to allow dynamic behaviors such as flying, mating, and feeding. When winged insects eclose into adults, their wings unfold, actuated hydraulically by hemolymph. Flowing hemolymph in the wing is necessary for functioning and healthy wings, both as the wing forms and as an adult. Because this process recruits the circulatory system, we asked, how much hemolymph is pumped into wings, and what happens to the hemolymph afterwards? Using Brood X cicadas ( Magicicada septendecim ), we collected 200 cicada nymphs, observing wing transformation over 2 h. Using dissection, weighing, and imaging of wings at set time intervals, we found that within 40 min after emergence, wing pads morphed into adult wings and total wing mass increased to ~ 16% of body mass. Thus, a significant amount of hemolymph is diverted from body to wings to effectuate expansion. After full expansion, in the ~ 80 min after, the mass of the wings decreased precipitously. In fact, the final adult wing is lighter than the initial folded wing pad, a surprising result. These results demonstrate that cicadas not only pump hemolymph into the wings, they then pump it out, producing a strong yet lightweight wing. 
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    Free, publicly-accessible full text available December 1, 2024
  8. Free, publicly-accessible full text available September 19, 2024