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    "headline": "Researchers Release Dataset for Sorting Shredded Black Plastics with Infrared Imaging",
    "dek": "A new dataset and machine learning framework enable automated sorting of shredded black industrial plastics using mid-wave infrared hyperspectral imaging.",
    "prose": "Automated sorting of shredded black plastics from end-of-life industrial waste presents a significant challenge in recycling facilities due to the limitations of current sensing and analytical approaches. [^1]\n\nThe authors introduced the first publicly available hyperspectral imaging dataset of shredded black plastics from end-of-life vehicles, comprising four industrial polymers across 13 co-registered RGB, VNIR, SWIR, and MWIR scenes. [^2]\n\nEleonora Alei and co-authors presented pyEDITH, a Python-based coronagraphic exposure time calculator for NASA's Habitable Worlds Observatory (HWO), in a paper accepted for publication in the RASTI HWO Special Issue. [^3]\n\nResearchers studied a six-qubit Lindblad model to determine the minimum number of Liouvillian spectral modes required to distinguish between amplitude damping and dephasing dissipative rates. [^4]\n\nThe study found that population modes within the spectrum contain no information regarding dephasing, which establishes a lower bound of D = 2^n retained modes for uniform dephasing identifiability. [^5]\n\npyEDITH simulates wavelength-dependent exposure times and signal-to-noise ratios (S/N) for synthetic Habitable Worlds Observatory (HWO) direct imaging observations, using realistic engineering specifications and user-defined target information. [^6]\n\nThe Habitable Worlds Observatory (HWO) is NASA's next recommended flagship mission tasked with searching for signs of habitability and life in dozens of nearby exoplanet systems. [^7]",
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