Results 161 to 170 of about 19,635 (294)

Error Correction Learning of Second Language Verbal Morphology: Associating Imperfect Contingencies in Naturalistic Frequency Distributions

open access: yesLanguage Learning, EarlyView.
Abstract We investigate what is learned from exposure to usage in verbal morphology using an error correction mechanism within an associative learning framework. We computationally simulated how second language (L2) learners would respond to naturalistic input of aspectual usage, characterized by “imperfect contingencies,” given two types of ...
Justyna Mackiewicz   +2 more
wiley   +1 more source

The association of artificial sweeteners intake and risk of cancer: an umbrella meta-analysis. [PDF]

open access: yesFront Med (Lausanne)
Abu-Zaid A   +13 more
europepmc   +1 more source

The Identity and Mineral Composition of Natural, Plant-Derived and Artificial Sweeteners. [PDF]

open access: yesMolecules, 2023
Leśniewicz A   +3 more
europepmc   +1 more source

Mosquito and arbovirus surveillance in wetlands of South‐East England: Comparison of two adult mosquito traps, use of a novel trap with FTA™ cards and arbovirus testing

open access: yesMedical and Veterinary Entomology, EarlyView.
Trap performance: Mosquito Magnet® captured significantly more mosquitoes overall, while BG‐Sentinel showed greater species evenness and was more effective for Culex pipiens s.l. and broader species representation. Spatial variation: Mosquito abundance and species composition varied significantly between wetlands, highlighting the importance of site ...
Alexander G. C. Vaux   +7 more
wiley   +1 more source

Artificial Sweeteners and Risk of Type 2 Diabetes in the Prospective NutriNet-Santé Cohort. [PDF]

open access: yesDiabetes Care, 2023
Debras C   +19 more
europepmc   +1 more source

Cheating or Competing? University Students’ Experience of AI Marketing and What It Means for AI Literacy Programming

open access: yesAnnals of Anthropological Practice, EarlyView.
ABSTRACT Given generative AI's rapid incursion into higher education, we examined how AI tools are marketed to US college students and how students experience AI promotions. Using a scalable action research model, we collected and analyzed 131 social media ads, 48 student interviews, and field notes compiled by three interns at student‐facing AI ...
Elisa J. Sobo   +3 more
wiley   +1 more source

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