scholarly journals Wegner Estimate for Random Divergence-Type Operators Monotone in the Randomness

2021 ◽  
Vol 24 (3) ◽  
Author(s):  
Alexander Dicke

AbstractIn this note, a Wegner estimate for random divergence-type operators that are monotone in the randomness is proven. The proof is based on a recently shown unique continuation estimate for the gradient and the ensuing eigenvalue liftings. The random model which is studied here contains quite general random perturbations, among others, some that have a non-linear dependence on the random parameters.

1991 ◽  
Vol 60 (6) ◽  
pp. 877-890 ◽  
Author(s):  
Martino Grandolfo ◽  
Maria Santini ◽  
Paolo Vecchia ◽  
Adalberto Bonincontro ◽  
Cesare Cametti ◽  
...  

1985 ◽  
Vol 50 (2) ◽  
pp. 538-550 ◽  
Author(s):  
Ernest Šturdík ◽  
Štefan Baláž ◽  
Marián Antalík ◽  
Pavol Sulo

Apparent partition coefficients in n-octanol-buffer system, solubility in the buffers, and retention by mitochondria from rat liver, by Mycobacterium phlei and by Saccharomyces cerevisiae (after 10 min incubation) have been characterized for 13 arylsubstituted phenylhydrazonopropanedinitrile derivatives. Regression analysis has shown linear dependence of logarithms of the apparent partition coefficients on the published π parameters characterizing lipophilicity of the substituents. The apparent partition coefficients are inversely proportional to the solubility of the phenylhydrazonopropanedinitriles. The retention by the biosystems studied increases linearly with increasing lipophilicity, being independent of reactivity of the phenylhydrazonopropanedinitriles. The non-linear dependence of concentration of the phenylhydrazonopropanedinitriles remaining in the medium on the lipophilicity indicates that a lipophilic-hydrophilic equilibrium is established in the given time. The retained amount of the derivatives tested decreases with increasing pH values. The dependences are Z-shaped and have been described by the equations derived from the model presented by application of non-linear regression analysis.


2017 ◽  
Vol 4 (3) ◽  
pp. 601-606 ◽  
Author(s):  
Sihame Bkhach ◽  
Olivier Alévêque ◽  
Yohann Morille ◽  
Tony Breton ◽  
Piétrick Hudhomme ◽  
...  

2020 ◽  
Vol 166 ◽  
pp. 108870
Author(s):  
E. Di Nardo ◽  
M. Marena ◽  
P. Semeraro

1994 ◽  
Vol 4 (2) ◽  
pp. 159-169 ◽  
Author(s):  
Teppo Martikainen ◽  
Vesa Puttonen ◽  
Martti Luoma ◽  
Timo Rothovius

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