Cross-sectional design and protocol for Artificial Intelligence Ready and Equitable Atlas for Diabetes Insights (AI-READI) by Gerald McGwin, Linda M Zangwill, Nicholas Evans, Shannon McWeeney, Cecilia S Lee, Bhavesh Patel, Jeffrey C Edberg, Cynthia Owsley, Aaron Lee, Cecilia Lee, Sally L Baxter, Michael Snyder, Samantha Hurst, Nicole Ehrhardt, Christopher Chute, Dawn S Matthies, Julia P Owen, Amir Bahmani, Sally Baxter, Edward Boyko, Aaron Cohen, Jorge Contreras, Garrison Cottrell, Virginia de Sa, Jeffrey Edberg, Irl Hirsch, Michelle Hribar, T.Y. Alvin Liu, Bonnie Maldenado, Sara Singer, Bradley Voytek, Joseph Yracheta, Linda Zangwill

“…There are three study sites: Birmingham, Alabama; San Diego, California; and Seattle, Washington.Ethics and dissemination AI-READI aims to establish standards, best practices and guidelines for collection, preparation and sharing of the data for the purposes of AI/ML, including guidance from bioethicists. …”
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A holistic review of nanomaterials in strain-hardening cementitious composites: Insights into micro- and macromechanical, deformation, smart, and durability properties by Isyaka Abdulkadir, Leong Sing Wong, Lee Woen Ean, G. Murali, Bashar S. Mohammed

“…Different types of NMs, such as nano silica (NS), and carbon-based nanomaterials—including carbon nanotubes/nanofibers (CNTs/NFs), graphene oxide (GO), and carbon black (CB)—influence SHCC behavior through multiple mechanisms. …”
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Bacterial profiling of mask waste from terrestrial and marine environment by A. Rakhmawati, B. Octavia, S. Marwati, D. Kristanti

“…Bacterial isolates were screened in a minimal salt medium supplemented with three types of masks (black duckbill, blue medical, white Korean filter) as the sole carbon and energy source at the various potential of hydrogen levels (5, 7, 9), temperatures (10, 30, 50 degrees Celsius), and sodium chloride concentrations (2.5, 5.0, 7.5 percent). …”
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A European aerosol phenomenology – 9: Light absorption properties of carbonaceous aerosol particles across surface Europe by Jordi Rovira, Marjan Savadkoohi, Gang I. Chen, Griša Močnik, Wenche Aas, Lucas Alados-Arboledas, Begoña Artiñano, Minna Aurela, John Backman, Sujai Banerji, David Beddows, Benjamin Brem, Benjamin Chazeau, Martine Collaud Coen, Cristina Colombi, Sebastien Conil, Francesca Costabile, Esther Coz, Joel F. de Brito, Kostas Eleftheriadis, Olivier Favez, Harald Flentje, Evelyn Freney, Asta Gregorič, Martin Gysel-Beer, Roy Harrison, Christoph Hueglin, Antti Hyvärinen, Matic Ivančič, Athina-Cerise Kalogridis, Hannes Keernik, Granakis Konstantinos, Paolo Laj, Eleni Liakakou, Chunshui Lin, Stefano Listrani, Krista Luoma, Marek Maasikmets, Hanna E. Manninen, Nicolas Marchand, Sebastiao Martins dos Santos, Saliou Mbengue, Nikos Mihalopoulos, Doina Nicolae, Jarkko V. Niemi, Michael Norman, Jurgita Ovadnevaite, Jean-Eudes Petit, Stephen Platt, André S.H. Prévôt, Manuel Pujadas, Jean-Philippe Putaud, Véronique Riffault, Martin Rigler, Matteo Rinaldi, Jaroslav Schwarz, Sanna Silvergren, Erik Teinemaa, Kimmo Teinilä, Hilkka Timonen, Gloria Titos, Anna Tobler, Jeni Vasilescu, Stergios Vratolis, Karl Espen Yttri, Eduardo Yubero, Naděžda Zíková, Andrés Alastuey, Tuukka Petäjä, Xavier Querol, Jesús Yus-Díez, Marco Pandolfi

“…Carbonaceous aerosols (CA), composed of black carbon (BC) and organic matter (OM), significantly impact the climate. …”
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The COVID‐19 pandemic and associated declines in cancer incidence by race/ethnicity and census‐tract level SES, rurality, and persistent poverty status by Benmei Liu, Mandi Yu, Jeffrey Byrne, Katheen A. Cronin, Eric J. Feuer

“…Results Overall, incidence rates decreased from 2015–2019 to 2020, with varying PCs by cancer sites and population groups. Notably, NH Blacks showed significantly larger PCs than NH Whites in female lung, prostate, and colon cancers (e.g., prostate cancer: NH Blacks −7.3, 95% CI: [−9.0, −5.5]; NH Whites: −3.1, 95% CI: [−3.9, −2.2]). …”
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Contextual Vulnerability Should Guide Fair Subject Selection in Xenotransplantation Clinical Trials by Gianna Strand

“…[xxi] Additionally, the medical records of Black patients are 2.5 times more likely to contain negative descriptors like non-compliant, non-adherent, aggressive, unpleasant, and hysterical than those of white patients.…”
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