Results 81 to 90 of about 28,888,705 (209)

Learning-based physical models of room-temperature semiconductor detectors with reduced data. [PDF]

open access: yesSci Rep, 2023
Banerjee S   +4 more
europepmc   +1 more source

Breach parameters for cascade dams’ breaks using physical, empirical and numerical modeling

open access: yesRBRH
The environmental, economic, and social consequences of dam breaks are catastrophic and require their prior knowledge to minimize risks. These consequences are directly related to rupture breach parameters, such as formation time and breach geometry ...
Rubens Gomes Dias Campos   +7 more
doaj   +1 more source

FROM QUANTUM PHYSICS TO PHYSICAL MODELS

open access: yesRomanian Journal of Neurology, 2017
As regards the issue of complexity, human brain is one of the most complex systems we know. The study of neural networks, their relation to the operation of single neurons and other important topics do and will profit a lot from complex systems approaches.
Gabriel Crumpei   +2 more
openaire   +1 more source

The Assessment of Physicochemical and Antimicrobial Properties of Hydrophilic Gels Containing Tetracycline Hydrochloride and Various Concentrations of Ethanol

open access: yesPharmaceutics
The high prevalence of acne, which affects nearly 85% of adolescents and young adults, underscores the importance of exploring new therapeutic solutions.
Agnieszka Kostrzębska   +3 more
doaj   +1 more source

“What standard should we set?”: A qualitative study of rehabilitation professionals’ perspectives on rehabilitation needs after traumatic injuries

open access: yesJournal of Rehabilitation Medicine
Objective: To assess rehabilitation professionals’ perspectives on unmet rehabilitation needs in patients with traumatic injuries and how to bridge the gap between met and unmet needs.
Emilie Isager Howe   +4 more
doaj   +1 more source

Scattering spectra models for physics

open access: yesPNAS Nexus
Abstract Physicists routinely need probabilistic models for a number of tasks such as parameter inference or the generation of new realizations of a field. Establishing such models for highly non-Gaussian fields is a challenge, especially when the number of samples is limited.
Sihao Cheng   +4 more
openaire   +4 more sources

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