Deep Residual Learning for Image Recognition
Actualmente diversas investigaciones se han enfocado en analizar a partir de videos de alta velocidad, características de las descargas eléctricas atmosféricas con el fin de adq...
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Generalized Gradient Approximation Made Simple
Generalized gradient approximations (GGA's) for the exchange-correlation energy improve upon the local spin density (LSD) description of atoms, molecules, and solids. We present...
Using thematic analysis in psychology
Increasingly, adult Indigenous language learners are being identified as the “missing generation” of learners who hold great potential to contribute to the revival of Indigenous...
Molecular cloning : a laboratory manual
Molecular Cloning has served as the foundation of technical expertise in labs worldwide for 30 years. No other manual has been so popular, or so influential. Molecular Cloning, ...
Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing
SUMMARY The common approach to the multiplicity problem calls for controlling the familywise error rate (FWER). This approach, though, has faults, and we point out a few. A diff...
Density-functional thermochemistry. III. The role of exact exchange
Despite the remarkable thermochemical accuracy of Kohn–Sham density-functional theories with gradient corrections for exchange-correlation [see, for example, A. D. Becke, J. Che...
ImageNet classification with deep convolutional neural networks
We trained a large, deep convolutional neural network to classify the 1.2 million high-resolution images in the ImageNet LSVRC-2010 contest into the 1000 different classes. On t...
Very Deep Convolutional Networks for Large-Scale Image Recognition
In this work we investigate the effect of the convolutional network depth on its accuracy in the large-scale image recognition setting. Our main contribution is a thorough evalu...
DNA sequencing with chain-terminating inhibitors
A new method for determining nucleotide sequences in DNA is described. It is similar to the “plus and minus” method [Sanger, F. & Coulson, A. R. (1975) J. Mol. Biol. 94, 441...
CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice
The sensitivity of the commonly used progressive multiple sequence alignment method has been greatly improved for the alignment of divergent protein sequences. Firstly, individu...
Scikit-learn: Machine Learning in Python
Scikit-learn is a Python module integrating a wide range of state-of-the-art machine learning algorithms for medium-scale supervised and unsupervised problems. This package focu...
The neighbor-joining method: a new method for reconstructing phylogenetic trees.
A new method called the neighbor-joining method is proposed for reconstructing phylogenetic trees from evolutionary distance data. The principle of this method is to find pairs ...