Variational Mode Decomposition
During the late 1990s, Huang introduced the algorithm called Empirical Mode Decomposition, which is widely used today to recursively decompose a signal into different modes of u...
Publications
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4,921 publications
Nonparametric Estimation from Incomplete Observations
Abstract In lifetesting, medical follow-up, and other fields the observation of the time of occurrence of the event of interest (called a death) may be prevented for some of the...
How mitochondria produce reactive oxygen species
The production of ROS (reactive oxygen species) by mammalian mitochondria is important because it underlies oxidative damage in many pathologies and contributes to retrograde re...
EFFECTS OF BIODIVERSITY ON ECOSYSTEM FUNCTIONING: A CONSENSUS OF CURRENT KNOWLEDGE
Humans are altering the composition of biological communities through a variety of activities that increase rates of species invasions and species extinctions, at all scales, fr...
Molecular Evolution and Phylogenetics
Abstract This book presents the statistical methods that are useful in the study of molecular evolution and illustrates how to use them in actual data analysis. Molecular evolut...
New Environmental Theories: Toward a Coherent Theory of Environmentally Significant Behavior
This article develops a conceptual framework for advancing theories of environmentally significant individual behavior and reports on the attempts of the author's research group...
WHO Declares COVID-19 a Pandemic.
The World Health Organization (WHO) on March 11, 2020, has declared the novel coronavirus (COVID-19) outbreak a global pandemic (1). At a news briefing , WHO Director-General, D...
Upper Echelons: The Organization as a Reflection of Its Top Managers
This analysis considers the impact of the top managers in an organization on the organization's outcomes, specifically strategic choices and performance levels. The focus is not...
Social Psychology of Intergroup Relations
A revolution in the science of emotion has emerged in recent decades, with the potential to create a paradigm shift in decision theories. The research reveals that emotions cons...
Unsupervised Representation Learning with Deep Convolutional Generative\n Adversarial Networks
In recent years, supervised learning with convolutional networks (CNNs) has\nseen huge adoption in computer vision applications. Comparatively, unsupervised\nlearning with CNNs ...