scholarly journals Enhanced Blind Calibration of Uniform Linear Arrays with One-Bit Quantization by Kullback-Leibler Divergence Covariance Fitting

Author(s):  
Amir Weiss ◽  
Arie Yeredor
2009 ◽  
Vol 89 (7) ◽  
pp. 1446-1456 ◽  
Author(s):  
Zhangmeng Liu ◽  
Zhitao Huang ◽  
Fenghua Wang ◽  
Yiyu Zhou

Author(s):  
Awtar Krishan

Earle's L-929 fibroblasts treated with mitosis-arresting but sub-lethal doses of vinblastine sulfate (VLB) show hypertrophy of the granular endoplasmic reticulum and annulate lamellae. Exposure of the cells to heavier doses of vincristine sulfate (VCR), a VLB-related drug, leads to the accumulation of large amounts of helical polyribosomes, Golgi membranes and crystals in the cytoplasm. In many of these cells a large number of helical polyribosomes are arranged in prominent linear rows, some of which may be up to 5 micrometers in length. Figure 1 shows a large array of helical polyribosomes near a crystalline mass (CRS) in an Earle's L-929 fibroblast exposed to VCR (5ϒ/ml.) for 3 hours At a higher magnification, as seen in figure 2, the helical polyribosomes are seen arranged in parallel rows. In favorably cut sections, a prominent backbone like "stalk" of finely granular material, measuring approximately 300Å in width is seen in close association with the linear rows of helical polyribosomes.


Author(s):  
Ryan Ka Yau Lai ◽  
Youngah Do

This article explores a method of creating confidence bounds for information-theoretic measures in linguistics, such as entropy, Kullback-Leibler Divergence (KLD), and mutual information. We show that a useful measure of uncertainty can be derived from simple statistical principles, namely the asymptotic distribution of the maximum likelihood estimator (MLE) and the delta method. Three case studies from phonology and corpus linguistics are used to demonstrate how to apply it and examine its robustness against common violations of its assumptions in linguistics, such as insufficient sample size and non-independence of data points.


2020 ◽  
Vol 15 (6) ◽  
pp. 517-527
Author(s):  
Yunyun Liang ◽  
Shengli Zhang

Background: Apoptosis proteins have a key role in the development and the homeostasis of the organism, and are very important to understand the mechanism of cell proliferation and death. The function of apoptosis protein is closely related to its subcellular location. Objective: Prediction of apoptosis protein subcellular localization is a meaningful task. Methods: In this study, we predict the apoptosis protein subcellular location by using the PSSMbased second-order moving average descriptor, nonnegative matrix factorization based on Kullback-Leibler divergence and over-sampling algorithms. This model is named by SOMAPKLNMF- OS and constructed on the ZD98, ZW225 and CL317 benchmark datasets. Then, the support vector machine is adopted as the classifier, and the bias-free jackknife test method is used to evaluate the accuracy. Results: Our prediction system achieves the favorable and promising performance of the overall accuracy on the three datasets and also outperforms the other listed models. Conclusion: The results show that our model offers a high throughput tool for the identification of apoptosis protein subcellular localization.


Sign in / Sign up

Export Citation Format

Share Document