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   https://doi.org/10.3847/1538-3881/ac9385  

   Lester, Kathryn V.; Schaefer, Gail H.; Fekel, Francis C.; Gies, Douglas R.; Henry, Todd J.; Jao, Wei-Chun; Paredes, Leonardo A.; Hubbard-James, Hodari-Sadiki; Farrington, Christopher D.; Gordon, Kathryn D.; et al (November 2022, The Astronomical Journal)

   Abstract We present the visual orbits of four spectroscopic binary stars, HD 61859, HD 89822, HD 109510, and HD 191692, using long baseline interferometry with the CHARA Array. We also obtained new radial velocities from echelle spectra using the APO 3.5 m, CTIO 1.5 m, and Fairborn Observatory 2.0 m telescopes. By combining the astrometric and spectroscopic observations, we solve for the full, three-dimensional orbits and determine the stellar masses to 1%–12% uncertainty and distances to 0.4%–6% uncertainty. We then estimate the effective temperature and radius of each component star through Doppler tomography and spectral energy distribution analyses. We found masses of 1.4–3.5 M ⊙ , radii of 1.5–4.7 R ⊙ , and temperatures of 6400–10,300 K. We then compare the observed stellar parameters to the predictions of the stellar evolution models, but found that only one of our systems fits well with the evolutionary models. 

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2. Orbital Refinement and Stellar Properties for the HD 9446, HD 43691, and HD 179079 Planetary Systems

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3. Accurate effective temperatures of the metal-poor benchmark stars HD 140283, HD 122563, and HD 103095 from CHARA interferometry

   https://doi.org/10.1093/mnrasl/sly010  

   Karovicova, I; White, T R; Nordlander, T; Lind, K; Casagrande, L; Ireland, M J; Huber, D; Creevey, O; Mourard, D; Schaefer, G H; et al (January 2018, Monthly Notices of the Royal Astronomical Society: Letters)
4. ADARE-HD: Adaptive-Resolution Framework for Efficient Object Detection and Tracking via HD-Computing

   Mejri, M; Amarnath, C; Chatterjee, A (August 2024, IEEE)

   Efficient and low-energy camera signal processing is critical for battery-supported sensing and surveillance applications. In this research, we develop a video object detection and tracking framework which adaptively down-samples frame pixels to minimize computation and memory costs, and thereby the energy consumed, while maintaining a high level of accuracy. Instead of always operating with the highest sensor pixel resolution (compute-intensive), video frame (pixel) content is down-sampled spatially, to adapt to changing camera environments (size of object tracked, peak-signal-tonoise- ratio (i.e, PSNR) of video frames). Object detection and tracking is supported by a novel video resolution-aware adaptive hyperdimensional computing framework. This leverages a low memory overhead non-linear hypervector encoding scheme specifically tailored for handling multiple degrees of resolution. Previous classification decisions of a moving object based on its tracking label are used to improve tracking robustness. Energy savings of up to 1.6 orders of magnitude and up to an order of magnitude compute speedup is obtained on a range of experiments performed on benchmark systems. 

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5. ALMA Detection of Extended Millimeter Halos in the HD 32297 and HD 61005 Debris Disks

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