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  1. Abstract

    Neural activity and learning lead to myelin sheath plasticity in the intact central nervous system (CNS), but this plasticity has not been well‐studied after CNS injury. In the context of spinal cord injury (SCI), demyelination occurs at the lesion site and natural remyelination of surviving axons can take months. To determine if neural activity modulates myelin and axon plasticity in the injured, adult CNS, we electrically stimulated the contralesional motor cortex at 10 Hz to drive neural activity in the corticospinal tract of rats with sub‐chronic spinal contusion injuries. We quantified myelin and axonal characteristics by tracing corticospinal axons rostral to and at the lesion epicenter and identifying nodes of Ranvier by immunohistochemistry. Three weeks of daily stimulation induced very short myelin sheaths, axon branching, and thinner axons outside of the lesion zone, where remodeling has not previously been reported. Surprisingly, remodeling was particularly robust rostral to the injury which suggests that electrical stimulation can promote white matter plasticity even in areas not directly demyelinated by the contusion. Stimulation did not alter myelin or axons at the lesion site, which suggests that neuronal activity does not contribute to myelin remodeling near the injury in the sub‐chronic period. These data are the first to demonstrate wide‐scale remodeling of nodal and myelin structures of a mature, long‐tract motor pathway in response to electrical stimulation. This finding suggests that neuromodulation promotes white matter plasticity in intact regions of pathways after injury and raises intriguing questions regarding the interplay between axonal and myelin plasticity.

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  2. Abstract

    We apply the color–magnitude intercept calibration method (CMAGIC) to the Nearby Supernova Factory SNe Ia spectrophotometric data set. The currently existing CMAGIC parameters are the slope and intercept of a straight line fit to the linear region in the color–magnitude diagram, which occurs over a span of approximately 30 days after maximum brightness. We define a new parameter,ωXY, the size of the “bump” feature near maximum brightness for arbitrary filtersXandY. We find a significant correlation between the slope of the linear region,βXY, in the CMAGIC diagram andωXY. These results may be used to our advantage, as they are less affected by extinction than parameters defined as a function of time. Additionally,ωXYis computed independently of templates. We find that current empirical templates are successful at reproducing the features described in this work, particularly SALT3, which correctly exhibits the negative correlation between slope and “bump” size seen in our data. In 1D simulations, we show that the correlation between the size of the “bump” feature andβXYcan be understood as a result of chemical mixing due to large-scale Rayleigh–Taylor instabilities.

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  3. Abstract We construct a physically parameterized probabilistic autoencoder (PAE) to learn the intrinsic diversity of Type Ia supernovae (SNe Ia) from a sparse set of spectral time series. The PAE is a two-stage generative model, composed of an autoencoder that is interpreted probabilistically after training using a normalizing flow. We demonstrate that the PAE learns a low-dimensional latent space that captures the nonlinear range of features that exists within the population and can accurately model the spectral evolution of SNe Ia across the full range of wavelength and observation times directly from the data. By introducing a correlation penalty term and multistage training setup alongside our physically parameterized network, we show that intrinsic and extrinsic modes of variability can be separated during training, removing the need for the additional models to perform magnitude standardization. We then use our PAE in a number of downstream tasks on SNe Ia for increasingly precise cosmological analyses, including the automatic detection of SN outliers, the generation of samples consistent with the data distribution, and solving the inverse problem in the presence of noisy and incomplete data to constrain cosmological distance measurements. We find that the optimal number of intrinsic model parameters appears to be three, in line with previous studies, and show that we can standardize our test sample of SNe Ia with an rms of 0.091 ± 0.010 mag, which corresponds to 0.074 ± 0.010 mag if peculiar velocity contributions are removed. Trained models and codes are released at 
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  4. Abstract

    We calibrate spectrophotometric optical spectra of 32 stars commonly used as standard stars, referenced to 14 stars already on the Hubble Space Telescope–based CALSPEC flux system. Observations of CALSPEC and non-CALSPEC stars were obtained with the SuperNova Integral Field Spectrograph over the wavelength range 3300–9400 Å as calibration for the Nearby Supernova Factory cosmology experiment. In total, this analysis used 4289 standard-star spectra taken on photometric nights. As a modern cosmology analysis, all presubmission methodological decisions were made with the flux scale and external comparison results blinded. The large number of spectra per star allows us to treat the wavelength-by-wavelength calibration for all nights simultaneously with a Bayesian hierarchical model, thereby enabling a consistent treatment of the Type Ia supernova cosmology analysis and the calibration on which it critically relies. We determine the typical per-observation repeatability (median 14 mmag for exposures ≳5 s), the Maunakea atmospheric transmission distribution (median dispersion of 7 mmag with uncertainty 1 mmag), and the scatter internal to our CALSPEC reference stars (median of 8 mmag). We also check our standards against literature filter photometry, finding generally good agreement over the full 12 mag range. Overall, the mean of our system is calibrated to the mean of CALSPEC at the level of ∼3 mmag. With our large number of observations, careful cross-checks, and 14 reference stars, our results are the best calibration yet achieved with an integral-field spectrograph, and among the best calibrated surveys.

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  5. null (Ed.)
  6. A public deep and wide science enabling survey will be needed to discover these black holes and supernovae, and to cover the area large enough for cosmic infrared background to be reliably studied. This enabling survey will find a large number of other transients and enable supernova cosmology up to z 5. 
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  7. In the next decade the peculiar velocities of SNe Ia in the local z<0.3 Universe will provide a measure of γ to ±0.01 precision that can definitively distinguish between General Relativity and leading models of alternative gravity. 
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  8. The Carnegie Supernova Project-II (CSP-II) was an NSF-funded, four-year program to obtain optical and near-infrared observations of a “Cosmology” sample of ˜100 Type Ia supernovae located in the smooth Hubble flow (0.03 ≲ z ≲ 0.10). Light curves were also obtained of a “Physics” sample composed of 90 nearby Type Ia supernovae at z ≤ 0.04 selected for near-infrared spectroscopic timeseries observations. The primary emphasis of the CSP-II is to use the combination of optical and near-infrared photometry to achieve a distance precision of better than 5%. In this paper, details of the supernova sample, the observational strategy, and the characteristics of the photometric data are provided. In a companion paper, the near-infrared spectroscopy component of the project is presented. 
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