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Lenz's law states that the direction of the electric current induced in a conductor by a changing magnetic field is such that the magnetic field created by the induced current opposes changes in the initial magnetic field. It is named after physicist Heinrich Lenz, who formulated it in 1834. [1]
Flux (also known as FLUX.1) is a text-to-image model developed by Black Forest Labs, based in Freiburg im Breisgau, Germany. Black Forest Labs were founded by former employees of Stability AI. As with other text-to-image models, Flux generates images from natural language descriptions, called prompts.
the constant is the permeability of free space, commonly called , divided by ; in the absence of magnetically reactive insulation the value 200 is exact when using the classical definition of μ 0 = 4π × 10 −7 H/m, and correct to 7 decimal places when using the 2019-redefined SI value of μ 0 = 1.256 637 062 12 (19) × 10 −6 H/m.
That is, the back-EMF is also due to inductance and Faraday's law, but occurs even when the motor current is not changing, and arises from the geometric considerations of an armature spinning in a magnetic field. This voltage is in series with and opposes the original applied voltage and is called "back-electromotive force" (by Lenz's law).
The rim thus becomes an electromagnet that resists rotation of the disc (an example of Lenz's law). On the far side of the figure, the return current flows from the rotating arm through the far side of the rim to the bottom brush.
Heinrich Friedrich Emil Lenz (German: [ˈeːmɪl ˈlɛnts]; also Emil Khristianovich Lenz; Russian: Эми́лий Христиа́нович Ленц; 12 February 1804 – 10 February 1865), usually cited as Emil Lenz [1] [2] or Heinrich Lenz in some countries, was an Estonian physicist who is most noted for formulating Lenz's law in electrodynamics in 1834.
Text-to-Image personalization is a task in deep learning for computer graphics that augments pre-trained text-to-image generative models. In this task, a generative model that was trained on large-scale data (usually a foundation model ), is adapted such that it can generate images of novel, user-provided concepts.
An image conditioned on the prompt an astronaut riding a horse, by Hiroshige, generated by Stable Diffusion 3.5, a large-scale text-to-image model first released in 2022. A text-to-image model is a machine learning model which takes an input natural language description and produces an image matching that description.
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