Publications
Explore 558 academic publications
Welcome to the Tidyverse
RESUMENEvaluación del efecto de un curso nivelatorio de matemáticas en educación superior: el caso de Matemáticas Básicas La investigación evalúa los efectos de tomar un curso d...
Development and testing of a general amber force field
Abstract We describe here a general Amber force field (GAFF) for organic molecules. GAFF is designed to be compatible with existing Amber force fields for proteins and nucleic a...
STRING v11: protein–protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets
Proteins and their functional interactions form the backbone of the cellular machinery. Their connectivity network needs to be considered for the full understanding of biologica...
Law and Finance
This paper examines legal rules covering protection of corporate shareholders and creditors, the origin of these rules, and the quality of their enforcement in 49 countries. The...
A Dynamic Theory of Organizational Knowledge Creation
This paper proposes a paradigm for managing the dynamic aspects of organizational knowledge creating processes. Its central theme is that organizational knowledge is created thr...
The Knowledge-Creating Company
Abstract How has Japan become a major economic power, a world leader in the automotive and electronics industries? What is the secret of their success? The consensus has been th...
A Simple, Positive Semi-Definite, Heteroskedasticity and Autocorrelation Consistent Covariance Matrix
This paper describes a simple method of calculating a heteroskedasticity and autocorrelation consistent covariance matrix that is positive semi-definite by construction. It also...
Can Quantum-Mechanical Description of Physical Reality Be Considered Complete?
In a complete theory there is an element corresponding to each element of reality. A sufficient condition for the reality of a physical quantity is the possibility of predicting...
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
Training Deep Neural Networks is complicated by the fact that the distribution of each layer's inputs changes during training, as the parameters of the previous layers change. T...