Comparison of simple potential functions for simulating liquid water
Classical Monte Carlo simulations have been carried out for liquid water in the NPT ensemble at 25 °C and 1 atm using six of the simpler intermolecular potential functions for t...
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1,479 publications
Highly accurate protein structure prediction with AlphaFold
Abstract Proteins are essential to life, and understanding their structure can facilitate a mechanistic understanding of their function. Through an enormous experimental effort ...
Basics of qualitative research : techniques and procedures for developing grounded theory
Part I: Introduction to Grounded Theory of Anselm Strauss Chapter 1: Inspiration and Background Chapter 2: Theoretical Foundations Chapter 3: Practical Considerations for Gettin...
Diffusion of Innovations 1
Contents Preface CHAPTER 1. ELEMENTS OF DIFFUSION CHAPTER 2. A HISTORY OF DIFFUSION RESEARCH CHAPTER 3. CONTRIBUTIONS AND CRITICISMS OF DIFFUSION RESEARCH CHAPTER 4. THE GENERAT...
Fully convolutional networks for semantic segmentation
Convolutional networks are powerful visual models that yield hierarchies of features. We show that convolutional networks by themselves, trained end-to-end, pixels-to-pixels, ex...
Absorptive Capacity: A New Perspective on Learning and Innovation
In this paper, we argue that the ability of a firm to recognize the value of new, external information, assimilate it, and apply it to commercial ends is critical to its innovat...
Glove: Global Vectors for Word Representation
Recent methods for learning vector space representations of words have succeeded in capturing fine-grained semantic and syntactic regularities using vector arithmetic, but the o...
Scoping studies: towards a methodological framework
This paper focuses on scoping studies, an approach to reviewing the literature which to date has received little attention in the research methods literature. We distinguish bet...
Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation
Object detection performance, as measured on the canonical PASCAL VOC dataset, has plateaued in the last few years. The best-performing methods are complex ensemble systems that...
Rethinking the Inception Architecture for Computer Vision
Convolutional networks are at the core of most state of-the-art computer vision solutions for a wide variety of tasks. Since 2014 very deep convolutional networks started to bec...
Squeeze-and-Excitation Networks
Convolutional neural networks are built upon the convolution operation, which extracts informative features by fusing spatial and channel-wise information together within local ...