PHAST. The Panchromatic Hubble Andromeda Southern Treasury. I. Ultraviolet and Optical Photometry of over 90 Million Stars in M31 by Zhuo Chen, Benjamin Williams, Dustin Lang, Andrew Dolphin, Meredith Durbin, Julianne J. Dalcanton, Adam Smercina, Léo Girardi, Claire E. Murray, Eric F. Bell, Martha L. Boyer, Richard D’Souza, Karoline Gilbert, Karl Gordon, Puragra Guhathakurta, Francois Hammer, L. Clifton Johnson, Tod R. Lauer, Margaret Lazzarini, Jeremiah W. Murphy, Ekta Patel, Amanda Quirk, Mariangelly Díaz Rodríguez, Julia Christine Roman-Duval, Robyn E. Sanderson, Anil Seth, Tobin M. Wainer, Daniel R. Weisz

“…We provide extensive analysis of the data quality, including artificial star tests to quantify completeness, photometric uncertainties, and flux biases, all of which vary due to the background source density and the number of overlapping exposures. …”
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The JADES Transient Survey: Discovery and Classification of Supernovae in the JADES Deep Field by Christa DeCoursey, Eiichi Egami, Justin D. R. Pierel, Fengwu Sun, Armin Rest, David A. Coulter, Michael Engesser, Matthew R. Siebert, Kevin N. Hainline, Benjamin D. Johnson, Andrew J. Bunker, Phillip A. Cargile, Stephane Charlot, Wenlei Chen, Mirko Curti, Shea DeFour-Remy, Daniel J. Eisenstein, Ori D. Fox, Suvi Gezari, Sebastian Gomez, Jacob Jencson, Bhavin A. Joshi, Sanvi Khairnar, Jianwei Lyu, Roberto Maiolino, Takashi J. Moriya, Robert M. Quimby, George H. Rieke, Marcia J. Rieke, Brant Robertson, Melissa Shahbandeh, Louis-Gregory Strolger, Sandro Tacchella, Qinan Wang, Christina C. Williams, Christopher N. A. Willmer, Chris Willott, Yossef Zenati

“…Even at z ≥ 2, the NIRCam data quality is high enough to allow SN classification via multiepoch light-curve fitting with confidence. …”
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Stroke Subtype Clustering by Multifractal Bayesian Denoising with Fuzzy C Means and K-Means Algorithms by Yeliz Karaca, Carlo Cattani, Majaz Moonis, Şengül Bayrak

“…Contrary to previous methods, our method embraces the following assets: (a) not applying the reduction of the stroke datasets’ attributes, leading to an efficient clustering comparison of stroke subtypes with the resulting attributes; (b) detecting attributes that eliminate “insignificant” irregularities while keeping “meaningful” singularities; (c) yielding successful clustering accuracy performance for enhancing stroke data qualities. Therefore, our study is a comprehensive comparative study with stroke datasets obtained from 2D multifractal denoised techniques applied for K-means and FCM clustering algorithms. …”
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