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  1. Free, publicly-accessible full text available January 1, 2024
  2. Free, publicly-accessible full text available September 1, 2023
  3. The increase of computer processing speed is significantly outpacing improvements in network and storage bandwidth, leading to the big data challenge in modern science, where scientific applications can quickly generate much more data than that can be transferred and stored. As a result, big scientific data must be reduced by a few orders of magnitude while the accuracy of the reduced data needs to be guaranteed for further scientific explorations. Moreover, scientists are often interested in some specific spatial/temporal regions in their data, where higher accuracy is required. The locations of the regions requiring high accuracy can sometimes be prescribed based on application knowledge, while other times they must be estimated based on general spatial/temporal variation. In this paper, we develop a novel multilevel approach which allows users to impose region-wise compression error bounds. Our method utilizes the byproduct of a multilevel compressor to detect regions where details are rich and we provide the theoretical underpinning for region-wise error control. With spatially varying precision preservation, our approach can achieve significantly higher compression ratios than single-error bounded compression approaches and control errors in the regions of interest. We conduct the evaluations on two climate use cases – one targeting small-scale, nodemore »features and the other focusing on long, areal features. For both use cases, the locations of the features were unknown ahead of the compression. By selecting approximately 16% of the data based on multi-scale spatial variations and compressing those regions with smaller error tolerances than the rest, our approach improves the accuracy of post-analysis by approximately 2 × compared to single-error-bounded compression at the same compression ratio. Using the same error bound for the region of interest, our approach can achieve an increase of more than 50% in overall compression ratio.« less
    Free, publicly-accessible full text available July 6, 2023
  4. Abstract

    Alzheimer’s disease (AD) manifested before age 65 is commonly referred to as early-onset AD (EOAD) (Reitz et al. Neurol Genet. 2020;6:e512). While the majority (> 90%) of EOAD cases are not caused by autosomal-dominant mutations inPSEN1,PSEN2, andAPP, they do have a higher heritability (92–100%) than sporadic late-onset AD (LOAD, 70%) (Wingo et al. Arch Neurol. 2012;69:59–64, Fulton-Howard et al. Neurobiol Aging. 2021;99:101.e1–101.e9). Although the endpoint clinicopathological changes, i.e., Aβ plaques, tau tangles, and cognitive decline, are common across EOAD and LOAD, the disease progression is highly heterogeneous (Neff et al. Sci Adv Am Assoc Adv Sci. 2021;7:eabb5398). This heterogeneity, leading to temporally distinct age at onset (AAO) and stages of cognitive decline, may be caused by myriad combinations of distinct disease-associated molecular mechanisms. We and others have used transcriptome profiling in AD patient-derived neuron models of autosomal-dominant EOAD and sporadic LOAD to identify disease endotypes (Caldwell et al. Sci Adv Am Assoc Adv Sci. 2020;6:eaba5933, Mertens et al. Cell Stem Cell. 2021;28:1533–1548.e6, Caldwell et al. Alzheimers Demen. 2022). Further, analyses of large postmortem brain cohorts demonstrate that only one-third of AD patients show hallmark disease endotypes like increased inflammation and decreased synaptic signaling (Neff et al. Sci Adv Am Assoc Advmore »Sci. 2021;7:eabb5398). Areas of the brain less affected by AD pathology at early disease stagessuch as the primary visual cortexexhibit similar transcriptomic dysregulation as those regions traditionally affected and, therefore, may offer a view into the molecular mechanisms of AD without the associated inflammatory changes and gliosis induced by pathology (Haroutunian et al. Neurobiol Aging. 2009;30:561–73). To this end, we analyzed AD patient samples from the primary visual cortex (19 EOAD, 20 LOAD) using transcriptomic signatures to identify patient clusters and disease endotypes. Interestingly, although the clusters showed distinct combinations and severity of endotypes, each patient cluster contained both EOAD and LOAD cases, suggesting that AAO may not directly correlate with the identity and severity of AD endotypes.

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  5. Abstract

    Two ultra-diffuse galaxies in the same group, NGC1052-DF2 and NGC1052-DF4, have been found to have little or no dark matter and to host unusually luminous globular cluster populations. Such low-mass diffuse objects in a group environment are easily disrupted and are expected to show evidence of tidal distortions. In this work, we present deep new imaging of the NGC1052 group, obtained with the Dragonfly Telephoto Array, to test this hypothesis. We find that both galaxies show strong position-angle twists and are significantly more elongated at their outskirts than in their interiors. The group’s central massive elliptical NGC1052 is the most likely source of these tidal disturbances. The observed distortions imply that the galaxies have a low total mass or are very close to NGC1052. Considering constraints on the galaxies’ relative distances, we infer that the dark matter halo masses of these galaxies cannot be much greater than their stellar masses. Calculating pericenters from the distortions, we find that the galaxies are on highly elliptical orbits, with a ratio of pericenter to present-day radiusRperi/R0∼ 0.1 if the galaxies are dark matter–free andRperi/R0∼ 0.01 if they have a normal dark halo. Our findings provide strong evidence, independent of kinematic constraints, thatmore »both galaxies are dark matter–deficient. Furthermore, the similarity of the tidal features in NGC1052-DF2 and NGC1052-DF4 strongly suggests that they arose at comparable distances from NGC1052. In Appendix A, we describesbcontrast, a robust method for determining the surface brightness limits of images.

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  6. Free, publicly-accessible full text available November 1, 2023
  7. Abstract We identify a ∼600 pc wide region of active star formation located within a tidal streamer of M82 via H α emission ( F H α ∼ 6.5 × 10 −14 erg s −1 cm −2 ), using a pathfinder instrument based on the Dragonfly Telephoto Array. The object is kinematically decoupled from the disk of M82 as confirmed via Keck/LRIS spectroscopy and is spatially and kinematically coincident with an overdensity of H i and molecular hydrogen within the “northern H i streamer” induced by the passage of M81 several hundred Myr ago. From H i data, we estimate that ∼5 × 10 7 M ⊙ of gas is present in the specific overdensity coincident with the H α source. The object’s derived metallicity (12+ log ( O / H ) ≃ 8.6 ), position within a gas-rich tidal feature, and morphology (600 pc diameter with multiple star-forming clumps), indicate that it is likely a tidal dwarf galaxy in the earliest stages of formation.