Results 191 to 200 of about 521,380 (323)

Phylogenetic analysis and the recognition of a new genus for Mexican Crassulaceae segregated from Echeveria

open access: yesTAXON, Volume 75, Issue 3, June 2026.
Abstract Systematic knowledge of the Mexican Crassulaceae is slowly progressing as data from new DNA regions and species sampling efforts increase. We compiled and generated new rbcL, matK, rps16, ITS/ITS2, and ETS DNA sequences and performed an updated phylogenetic reconstruction for a group of 131 Mexican Crassulaceae terminals from 11 of the 13 ...
Luis Emilio de la Cruz‐López   +1 more
wiley   +1 more source

CP invariance in the reaction at 1.546 GeV/c

open access: yes, 1987
P. Barnes   +28 more
semanticscholar   +1 more source

The United States Magnetotelluric Array and the National Impedance Map

open access: yesReviews of Geophysics, Volume 64, Issue 2, June 2026.
Abstract The United States Magnetotelluric Array (USMTArray) data set, collected in the years 2006–2024, consists of more than 1,700 long‐period magnetotelluric stations covering the entirety of the contiguous United States on a quasi‐regular 70 km grid.
Anna Kelbert   +7 more
wiley   +1 more source

The First Archaeomagnetic Age at Tiwanaku and Implications for Dating Andean Metallurgical Furnaces

open access: yesArchaeometry, Volume 68, Issue 3, Page 317-329, June 2026.
ABSTRACT This paper presents the first archaeomagnetic dating at Tiwanaku (Andean Altiplano). We compared the geomagnetic field values recorded by a metallurgical furnace against an updated SHAWQ2k‐SH global model and a regional intensity curve, both of which include, for the first time, high‐quality intensity data from the Southern Hemisphere. Results
Judit del Río   +6 more
wiley   +1 more source

Fairness at Risk: Where Bias Emerges in Machine Learning

open access: yesExpert Systems, Volume 43, Issue 6, June 2026.
ABSTRACT Artificial intelligence and machine learning (ML) now shape decisions in healthcare, finance and security, but they can reproduce historical prejudice and inequality. Bias in training data and in model implementation can amplify harm, especially for racial and gender minorities.
Otavio de Paula Albuquerque   +2 more
wiley   +1 more source

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