The fluorescence decay curves were fitted with a bi-exponential fluorescence decay model by iterative IRF- reconvolution to extract the characteristic lifetimes and weights of the GFP designs. Photobleaching. Photobleaching was measured similarly as pre- viously described73. A final concentration of 1 ...
\end{aligned}$$ would encompass quantum ergodicity in the benjamini–schramm limit. slightly weaker results of this form concerning quantum ergodicity in the benjamini–schramm limit hold for more general sequences of locally symmetric spaces due to work of le masson and sahlsten on \(\mathbb {...
FUNCTIONS 50:34 NICOLE RAULF_ AUTOMORPHIC FORMS AND QUANTUM UNIQUE ERGODICITY 54:27 IAN PETROW_ WEYL SUBCONVEXITY, GENERALIZED PGL_2 KUZNETSOV FORMULAS, AND OPTIMAL 1:04:30 446 1:05:25 A MIXED-NORM ESTIMATE OF TWO-PARTICLE REDUCED DENSITY MATRIX OF MANY-BODY SCHRÖD 46:42 A NON-...
(tapping mode). Images of 2 µm scan size were acquired with asiliconprobe for soft tapping mode (FMV-A Bruker, spring constant 2.8 Nm−1, resonance frequency 78 kHz). Lateral dimensions evaluation was performed by convolution, assuming the nominal radius of curvature (8 nm) is ...
5b). To illustrate the feature extraction process, we visualized 16 convolutional filters from the first convolutional layer of the second convolutional block of VGG-16 (Fig. 5c). We also plotted the intermediate feature maps extracted from the 16 convolutions (Fig. 5d). Fig. 5 Module 3: ...
(1) Train four CNNs on the Icelandic dataset on the four previously mentioned image types. (2) Freeze convolutions layers and train the CNNs on the IXI dataset (transfer learning step). (3) Predict brain age in the UK Biobank dataset using CNNs, combine the predictions with majority ...
TheDirichlet convolutionMathMLof two arithmetic functionsMathMLis defined in the usual fashion as MathML Distribution estimates on arithmetic functions As mentioned in the introduction, a key ingredient in the Goldston-Pintz-Yıldırım approach to small gaps between primes comes from distribution...
Finally, we choose the optimal loss functions and optimize the training process. Dataset description In this paper, we test our proposed models on two real-world datasets. One dataset is collected from Beijing city, which is the capital of China, while the other dataset is collected from Xi’...
This paper explores the utility of a discrete singular convolution (DSC) algorithm for the integration of the sine-Gordon equation. The initial values are chosen close to a homoclinic manifold for which previous methods have encountered significant numerical difficulties such as numerically induced spatia...
Briefly, CHiCAGO calls interactions based on a convolution background model reflecting both ‘Brownian’ (real, but expected interactions) and ‘technical’ (assay and sequencing artifacts) components. The resulting p values are adjusted using a weighted false discovery control procedure that specifically...