Your English writing platform
Discover LudwigExact(1)
To get finite results, it is necessary to introduce a finite damping.
Similar(11)
It turned out that if we start with residually finite semigroups from Sect. 3, we often get residually finite finitely presented groups whose Dehn and depth functions resemble the corresponding functions of the semigroups we start with.
end{aligned} This contradicts (26) and we get the finite time blow-up result.
According to Eq. (3), the velocity should be equal to zero in this case, unless the interfacial mobility → ∞ to get a finite migration velocity.
Therefore we get a finite sum begin{aligned} sum K_m le mathrm {const} times sum _{n=0}^infty n^{p+d-1} lambda _mathrm {min}^{-n} < infty.
Multiplying by −1 and taking into account the fact that both ω ( t ) and p α ( σ ( t ) ) φ ( t ) τ ′ ( t ) v ( t ) are nonnegative we get a finite upper bound for the integral from (15), which contradicts (15).
We will get a finite value of the above limit because numerator is a polynomial in x having terms of degree less than or equal to four and (f,f',f" in C_{1+x^{2}}^{0}).
It is easy to see that the distortion function of N in G is at least as large as the Dehn function in Q, so choosing Q properly one can get a finitely presented residually finite group G with a highly distorted subgroup N. Now, the subgroup N is normal in the HNN extension T. So it is closed in the pro-finite topology of T only if (Q=G/N) is residually finite.
Samples of input variables and the corresponding response, which all together serve as the inputs of Kriging approximation, are gotten through finite element simulations based on the design of experiments.
"Obviously they've got a finite amount of budget for those — they need to find a way to be able to best deploy those… And the challenge that they have is they don't have a lot of information on people as they start through this funnel — and so they have what is a classic 'cold start' problem in machine learning.
You've got a finite amount of physical and emotional energy.
Write better and faster with AI suggestions while staying true to your unique style.
Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com