Results 111 to 120 of about 10,978,845 (289)

Ultra-low frequency energy harvesting using bi-stability and rotary-translational motion in a magnet-tethered oscillator

open access: yes, 2020
Harvesting ultra-low frequency random vibration, such as human motion or turbine tower oscillations, has always been a challenge, but could enable many potential self-powered sensing applications.
Ben Gunn (2870369)   +4 more
core   +2 more sources

An approach to low noise amplifier optimization in Advanced Design System CAD

open access: yesБезопасность информационных технологий, 2016
An approach to silicon low noise amplifier (LNA) optimization, intended for use in the CAD Advanced Design System, has been presented. The approach is based on a technique using the contour plots of LNA parameters such as operating current, transistor ...
Galina Nikolaevna Nazarova   +2 more
doaj  

Elevated liver enzymes is not an impediment to allopurinol dose escalation: an observational cohort study

open access: yesArthritis Care &Research, Accepted Article.
Objective Routine liver enzyme monitoring is advocated while on allopurinol but supporting guidance is lacking. We assessed the incidence and factors associated with elevated liver enzymes in gout patients commenced on allopurinol. Methods 150 patients with gout and normal baseline serum aminotransferases initiated on allopurinol were followed ...
May Shuen Tang   +4 more
wiley   +1 more source

Synchronous assessment of CSF and cerebral arteriovenous flow interactions across ultra-low, low, respiratory, and cardiac frequencies using real-time phase-contrast MRI

open access: yesNeuroImage
Cerebrospinal fluid (CSF) oscillations are traditionally viewed as passive responses to cardiac-driven cerebral blood volume (CBV) fluctuations. However, the origins of their respiratory, low-, and ultra-low-frequency components remain unclear.
Pan Liu   +5 more
doaj   +1 more source

What Do Large Language Models Know About Materials?

open access: yesAdvanced Engineering Materials, EarlyView.
If large language models (LLMs) are to be used inside the material discovery and engineering process, they must be benchmarked for the accurateness of intrinsic material knowledge. The current work introduces 1) a reasoning process through the processing–structure–property–performance chain and 2) a tool for benchmarking knowledge of LLMs concerning ...
Adrian Ehrenhofer   +2 more
wiley   +1 more source

Ultra-low Frequency Acoustic Luneburg Lens

open access: yes
In this paper, a novel structural Luneburg lens with local resonators is proposed. This lens allows for the realization of subwavelength focusing in low frequency range. The lens is achieved by graded refractive index from the lens centre to the outer surface.
Zhao, Liuxian   +4 more
openaire   +2 more sources

Symbolic Regression and Multi‐Objective Optimization of the Flory–Huggins Interaction Parameter for Hydrogels

open access: yesAdvanced Engineering Materials, EarlyView.
We develop a data‐driven method to derive the mathematical expressions of the Flory–Huggins interaction parameter χ for the swelling behavior of temperature–responsive hydrogels. Starting from initial assumptions of χ, our workflow combines Bayesian optimization, Flory–Rehner theory, and symbolic regression to generate candidate χ expressions.
Yawen Wang   +2 more
wiley   +1 more source

Optimization of the Production of Rubber Compounds Using Mathematical Models

open access: yesAdvanced Engineering Materials, EarlyView.
Rubber compounds were mixed in a batch internal mixer, and symbolic regression was used to derive mathematical models linking recipe and process parameters to ram path, torque, and mixing quality (incorporation, dispersion, distribution). Subsequent optimization with evolutionary algorithms identified operating conditions that reduce specific energy ...
Anke Bardehle   +7 more
wiley   +1 more source

Ultra-Low-Dimensional Embeddings for Doubling Metrics

open access: yes, 2018
We consider the problem of embedding a metric into low-dimensional Euclidean space. The classical theorems of Bourgain and of Johnson and Lindenstrauss imply that any metric on n points embeds into an O(log n)-dimensional Euclidean space with O(log n ...
Kunal Talwar (5414963)   +2 more
core   +1 more source

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