Results 171 to 180 of about 46,930 (256)
Spatial hearing training in virtual reality with simulated asymmetric hearing loss. [PDF]
Valzolgher C +5 more
europepmc +1 more source
Abstract The use of different coaching models can provide an effective environment for skill learning. The Anatomical Donor Stewardship (ADS) Coaching subcommittee, within the Human Anatomy and Physiology Society (HAPS), developed and held an inaugural Coaching workshop for human anatomical dissection for HAPS members at the 2025 HAPS Annual Conference
Danielle N. Edwards +6 more
wiley +1 more source
SPATIAL HEARING IN PATIENTS WITH SENSORINEURAL HEARING LOSS
openaire +1 more source
Designing and evaluating a neuroanatomy learning experience using multiple external representations
Abstract Neuroanatomy is challenging, requiring multiple external representations (MER) for comprehension. While studies have examined individual representations of neuroanatomy, a gap remains in understanding how students link across MER, especially between technology‐generated representations with everyday experiences.
Valeria Vendries, Ji Shen
wiley +1 more source
Reversible inactivation of ferret auditory cortex impairs spatial and non-spatial hearing
Town SM, Poole KC, Wood KC, Bizley JK.
europepmc +1 more source
Spatial Hearing by Bilateral Cochlear Implant Users With Temporal Fine-Structure Processing. [PDF]
Ausili SA +9 more
europepmc +1 more source
Abstract Caste—an ascriptive social hierarchy in South Asia and its diaspora—is a globalized phenomenon. Recent caste‐based discrimination, particularly in technology companies and anti‐caste efforts to address it, has compelled academia, policy, and the technology industry to better understand contemporary mechanics of caste.
Nayana Kirasur, Britt Paris
wiley +1 more source
Electro-Haptic Enhancement of Spatial Hearing in Cochlear Implant Users. [PDF]
Fletcher MD, Cunningham RO, Mills SR.
europepmc +1 more source
Abstract Information science rests on a compact: its mediating signs maintain a traceable relation to what they describe. Large language models (LLMs) break it architecturally, generating discourse that is statistically plausible yet epistemically ungrounded, while standard metrics (precision, recall, relevance) cannot detect the rupture.
Martin Thellefsen, Alon Friedman
wiley +1 more source

