Results 131 to 140 of about 11,095,741 (334)

Digital numerically controlled oscillator [PDF]

open access: yes, 1980
The frequency and phase of an output signal from an oscillator circuit are controlled with accuracy by a digital input word. Positive and negative alterations in output frequency are both provided for by translating all values of input words so that they
Cellier, A., Huey, D. C., Ma, L. N.
core   +1 more source

A Twist in the Diagnosis: Chronic Arthropathy Without Inflammation

open access: yes
Arthritis Care &Research, EarlyView.
María Á. Puche‐Larrubia   +3 more
wiley   +1 more source

Unrolling of Syngonium podophyllum: Functional Anatomy, Morphology and Modelling of Its Peltate Leaves

open access: yesAdvanced Biology, EarlyView.
The unrolling of the peltate leaves in Syngonium podophyllum is analyzed and quantified (left‐hand side to center). These measurements serve to verify a mathematical model for leaf unrolling based on the model used in Schmidt (2007). An additional formula for obtaining a layer mismatch from a prescribed radius is derived.
Michelle Modert   +4 more
wiley   +1 more source

The OU goes digital [PDF]

open access: yes, 2003
Describes how the Open University is embedding electronic library resources and services into e ...
Ramsden, Anne
core  

Soft‐Layered Composites with Wrinkling‐Activated Multi‐Linear Elastic Behavior, Stress Mitigation, and Enhanced Strain Energy Storage

open access: yesAdvanced Engineering Materials, EarlyView.
In this study, exciting new bi‐/multi‐linear elastic behavior of soft elastic composites that accompany the activation of wrinkling in the embedded interfacial layers is analyzed. The new features and performance of these composite materials, including dramatic enhancements in energy storage, can be tailored by the concentration of interfacial layers ...
Narges Kaynia   +2 more
wiley   +1 more source

Beyond Order: Perspectives on Leveraging Machine Learning for Disordered Materials

open access: yesAdvanced Engineering Materials, EarlyView.
This article explores how machine learning (ML) revolutionizes the study and design of disordered materials by uncovering hidden patterns, predicting properties, and optimizing multiscale structures. It highlights key advancements, including generative models, graph neural networks, and hybrid ML‐physics methods, addressing challenges like data ...
Hamidreza Yazdani Sarvestani   +4 more
wiley   +1 more source

Race representation matters in cancer care

open access: yesThe Lancet: Digital Health, 2021
The Lancet Digital Health
doaj   +1 more source

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