134,366 research outputs found

    Dataset to support: "Quantifying photoluminescence variability in monolayer molybdenum disulfide films grown by chemical vapour deposition"

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    Monolayer molybdenum disulfide (MoS2) is a promising candidate for inclusion in optoelectronic technologies, owing to its two-dimensional (2D) nature and resultant novel photoluminescence (PL). Chemical vapour deposition (CVD) is an important method for the preparation of large-area films of monolayer MoS2. The PL character of as-prepared monolayer MoS2 must be well understood to facilitate detailed evaluation of any process-induced effects during device fabrication. We comparatively explore the PL emission from four different commercially available CVD-grown MoS2 monolayer films. We characterize the samples via Raman and PL spectroscopy, using both single-spot and mapping techniques, while atomic force microscopy (AFM) is applied to map the surface structure. Via multipeak fitting, we decompose the PL spectra into constituent exciton and trion contributions, enabling an assessment of the quality of the MoS2 monolayers. We find that the PL character varies significantly from sample to sample. We also reveal substantial inhomogeneity of the PL signal across each individual MoS2 film. We attribute the PL variation to non-uniform MoS2 film morphologies that result from the nucleation and coalescence processes during the CVD film development. Understanding the large variability in starting PL behaviour is vital to optimize the optoelectronic properties for MoS2-based devices

    Translation of tissue-based artificial intelligence into clinical practice: from discovery to adoption.

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    Digital pathology (DP), or the digitization of pathology images, has transformed oncology research and cancer diagnostics. The application of artificial intelligence (AI) and other forms of machine learning (ML) to these images allows for better interpretation of morphology, improved quantitation of biomarkers, introduction of novel concepts to discovery and diagnostics (such as spatial distribution of cellular elements), and the promise of a new paradigm of cancer biomarkers. The application of AI to tissue analysis can take several conceptual approaches, within the domains of language modelling and image analysis, such as Deep Learning Convolutional Neural Networks, Multiple Instance Learning approaches, or the modelling of risk scores and their application to ML. The use of different approaches solves different problems within pathology workflows, including assistive applications for the detection and grading of tumours, quantification of biomarkers, and the delivery of established and new image-based biomarkers for treatment prediction and prognostic purposes. All these AI formats, applied to digital tissue images, are also beginning to transform our approach to clinical trials. In parallel, the novelty of DP/AI devices and the related computational science pipeline introduces new requirements for manufacturers to build into their design, development, regulatory and post-market processes, which may need to be taken into account when using AI applied to tissues in cancer discovery. Finally, DP/AI represents challenge to the way we accredit new diagnostic tools with clinical applicability, the understanding of which will allow cancer patients to have access to a new generation of complex biomarkers

    Coastal pelagic fish functional group time series as both ecosystem model output and independent estimates.

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    Independently derived estimates (blue points; blue lines = locally estimated scatterplot smoothing lines) of relative biomass of sardine, anchovy, jack mackerel, and Pacific chub mackerel via stock assessments [56, 84, 86, 87] are plotted against ecosystem model-derived estimates of matching functional groups (black lines).</p

    Seabird and mammal functional group time series as both ecosystem model output and independent estimates.

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    Independently derived estimates (blue lines and points) of relative biomass via a Juvenile Salmon and Ocean Ecosystem Survey (JSOES; common murre and sooty shearwaters), a humpback whale mark-recapture study (baleen whales [88]), and counts of the well-monitored Southern resident killer whale population [https://www.whaleresearch.com/orca-population] are plotted against ecosystem model-derived estimates of matching functional groups (black lines).</p

    De Novo Green Fluorescent Protein Chromophore-Based Probes for Capturing Latent Fingerprints Using a Portable System

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    Rapid visualization of latent fingerprints, preferably at their point of origin, is essential for effective crime scene evaluation. Here, we present a new class of green fluorescent protein chromophore-based fluorescent dyes (LFP-Yellow and LFP-Red) that can be used for real-time visualization of LFPs within 10 s. Compared with traditional chemical reagents for LFPs, these fluorescent dyes are completely water-soluble, exhibit low cytotoxicity, and are harmless to users. Level 1–3 details of the LFPs could be clearly revealed through “off–on” fluorescence signal readout. Additionally, the fluorescent dyes were constructed based on an imidazolinone core and so do not contain pyridine groups or metal ions, which ensures that the DNA is not contaminated during extraction and identification after the LFPs are treated with the dyes. Combined with our as-developed portable system for capturing LFPs, LFP-Yellow and LFP-Red enabled the rapid capture of LFPs. Therefore, these green fluorescent protein chromophore-based probes provide an approach for the rapid identification of individuals who were present at a crime scene

    DataSheet_1_Use of satellite imagery to estimate distribution and abundance of Cumberland Sound beluga whales reveals frequent use of a glacial river estuary.docx

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    Limiting disturbance in critical habitats is an important part of ensuring the well-being and sustainability of populations at risk, such as Cumberland Sound beluga whales (Delphinapterus leucas). Using non-disruptive Very High Resolution (VHR) satellite imagery, an emerging tool in cetacean monitoring, we aimed to estimate summer abundance and identify critical habitat for Cumberland Sound beluga whales. Specifically we looked in fiords that comprise their summer distribution, such as Clearwater Fiord where there is a large estuary, an important habitat to many beluga populations. Satellite images of the area were collected in 2020 and 2021, at 30 cm resolution, and in 2022 at 50 cm resolution. We evaluated beluga whale distribution using Kernel density, and identified critical habitats as areas consistently part of the beluga whale core distribution across years. Clearwater Fiord abundance estimates were corrected for whales that were too deep to be identified in the images. The estimates were significantly lower in 2021 (197 whales, 95%CI: 180-216) and 2022 (194 whales, 95%CI: 172-218) compared to 2020 (393 whales, 95%CI: 366-422). Other fiords were only imaged in 2021 and 2022, resulting in average corrected abundance estimates for all fiords of 462 (95% CI: 425-502) and 252 (95%CI: 226-280) beluga whales, respectively. Downsampling of 30 cm images to 50 cm resulted in up to 45% fewer whales detected. The only critical habitat identified within the summer distribution was in Clearwater Fiord, in or near the estuary freshwater plume and in a bay to the west of the plume. The identified critical habitats should be areas of consideration in the continued discussion on the protection and sustainability of the Cumberland Sound beluga whale population.</p

    The Dark Energy Survey Supernova Program: Cosmological Analysis and Systematic Uncertainties

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    International audienceWe present the full Hubble diagram of photometrically-classified Type Ia supernovae (SNe Ia) from the Dark Energy Survey supernova program (DES-SN). DES-SN discovered more than 20,000 SN candidates and obtained spectroscopic redshifts of 7,000 host galaxies. Based on the light-curve quality, we select 1635 photometrically-identified SNe Ia with spectroscopic redshift supernovae by a factor of five. In a companion paper, we present cosmological results of the DES-SN sample combined with 194 spectroscopically-classified SNe Ia at low redshift as an anchor for cosmological fits. Here we present extensive modeling of this combined sample and validate the entire analysis pipeline used to derive distances. We show that the statistical and systematic uncertainties on cosmological parameters are σΩM,stat+sysΛCDM=\sigma_{\Omega_M,{\rm stat+sys}}^{\Lambda{\rm CDM}}=0.017 in a flat Λ\LambdaCDM model, and (σΩM,σw)stat+syswCDM=(\sigma_{\Omega_M},\sigma_w)_{\rm stat+sys}^{w{\rm CDM}}=(0.082, 0.152) in a flat wwCDM model. Combining the DES SN data with the highly complementary CMB measurements by Planck Collaboration (2020) reduces uncertainties on cosmological parameters by a factor of 4. In all cases, statistical uncertainties dominate over systematics. We show that uncertainties due to photometric classification make up less than 10% of the total systematic uncertainty budget. This result sets the stage for the next generation of SN cosmology surveys such as the Vera C. Rubin Observatory's Legacy Survey of Space and Time

    GWTC-2.1: Deep extended catalog of compact binary coalescences observed by LIGO and Virgo during the first half of the third observing run

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    International audienceThe second Gravitational-Wave Transient Catalog, GWTC-2, reported on 39 compact binary coalescences observed by the Advanced LIGO and Advanced Virgo detectors between 1 April 2019 15∶00 UTC and 1 October 2019 15∶00 UTC. Here, we present GWTC-2.1, which reports on a deeper list of candidate events observed over the same period. We analyze the final version of the strain data over this period with improved calibration and better subtraction of excess noise, which has been publicly released. We employ three matched-filter search pipelines for candidate identification, and estimate the probability of astrophysical origin for each candidate event. While GWTC-2 used a false alarm rate threshold of 2 per year, we include in GWTC-2.1, 1201 candidates that pass a false alarm rate threshold of 2 per day. We calculate the source properties of a subset of 44 high-significance candidates that have a probability of astrophysical origin greater than 0.5. Of these candidates, 36 have been reported in GWTC-2. We also calculate updated source properties for all binary black hole events previously reported in GWTC-1. If the eight additional high-significance candidates presented here are astrophysical, the mass range of events that are unambiguously identified as binary black holes (both objects ≄3M⊙) is increased compared to GWTC-2, with total masses from ∌14M⊙ for GW190924_021846 to ∌182M⊙ for GW190426_190642. Source properties calculated using our default prior suggest that the primary components of two new candidate events (GW190403_051519 and GW190426_190642) fall in the mass gap predicted by pair-instability supernova theory. We also expand the population of binaries with significantly asymmetric mass ratios reported in GWTC-2 by an additional two events (the mass ratio is less than 0.65 and 0.44 at 90% probability for GW190403_051519 and GW190917_114630 respectively), and find that two of the eight new events have effective inspiral spins χeff&gt;0 (at 90% credibility), while no binary is consistent with χeff&lt;0 at the same significance. We provide updated estimates for rates of binary black hole and binary neutron star coalescence in the local Universe

    <i>CYP26A1/B1/C1</i> expression during fetal retinal development and organoid differentiation experiments.

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    (A–C) Expression of CYP26A1, CYP26B1, and CYP26C1 in fetal human retinas by day of gestation and retinal region. CPM, log counts per million. Analyzed from [16]. Error bars for the 2 samples from fetal day 94 indicate SEM. Original data sets are in S3 Data. (A) Whole retina. (B) Central retina. (C) Periphery. (D) Protocol for human retinal organoid differentiation, adapted from [15]. (E) Expression of THRB (cone marker) and NRL (rod marker) during retinal organoid development. TPM, transcripts per million. Analyzed from [15]. Original data sets are in S6 Data. (F) No significant differences in overall densities of M + L cones at day 200 in early RA treatment conditions (as in Fig 3F–3H) (Dunnett’s multiple comparison’s test, against “No RA” control: “RA to day 60” p = 0.98, “RA to day 130” p = 0.32). Significant difference between “No RA” and “Late RA” conditions (Dunnett’s multiple comparison’s test, * indicates p Fig 3I). Error bars indicate SEM. Individual circles represent individual organoids. Original data sets are in S3 Data. (G) Representative brightfield image of a retinal organoid in “RA to day 130” conditions. (H) Representative brightfield image of a retinal organoid in “Late RA” conditions. (PDF)</p