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It is easy to verify that, when the network is fully separable for all topic pairs, (sigma (S,p)) is 1-sub-additive.
It is easy to verify that, when η and ν are convex functions, the transmitter impairment constraints (eta ({{left | {{mathbf {T}}_{n}}{{mathbf {W}}_{m}} right |}_{F}})le {{t}_{m,n}}) and the receiver impairment constraints (nu left (sqrt {{sum nolimits }_{m}{left | mathbf {h}_{m,i,j}^{H}{{mathbf {W}}_{m}} right |}_{F}^{2}}right)le {{r}_{i,j}}) are both convex constraints.
And we also verify that when the recording frequency is reduced to the optimal frequency compared to the high frequency recorded original signals, the accuracy of the SOC estimation is not influenced.
It is easy to verify that when the network is fully separable among all topics, (G_i) and (G_j) are disconnected for any (ine j).
It is easy to verify that when
The paper is organized as follows: In the next section, we obtain the threshold value (tau_{0}) and verify that when (0leqtau
Similar(51)
Note that is upper semicontinuous when and is upper semicontinuous when, and it is easy to verify that is also upper semicontinuous when, where denotes the boundary of.
Similarly, by letting and, one can verify that contains nonreal eigenvalues when.
It is easy to verify that assumption (H2) holds when setting (L=1).
To verify that Mos1Env was immunogenic when expressed from the clinical candidate rcAd26.dE3.dE4.Mos1Env, BALB/c mice (n = 4) were immunized either intramuscularly or intranasally with a single administration of 1 × 10 vp of the clinical candidate rcAd26.dE3.dE4.Mos1Env vector or replication-incompetent vector ri(E1−).Ad26.dE3.Mos1Env.Ad26.dE3.Mos1Env
But that's not a huge issue since many carriers already verified that when they installed their Wi-Fi systems.
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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