PLoS ONE

PLoS ONE is an open access peer-reviewed scientific journal published by the Public Library of Science (PLoS) since 2006. It covers primary research from any discipline within science and medicine. All submissions go through an internal and external pre-publication peer review but are not excluded on the basis of lack of perceived importance or adherence to a scientific field. The PLoS ONE online platform has post-publication user discussion and rating features. PLoS ONE was launched in December 2006 as a beta version. It launched with Commenting and Note making functionality, and added the ability to rate articles in July 2007. In September 2007 the ability to leave "trackbacks" on articles was added. In August 2008 it moved from a weekly publication schedule to a daily one, publishing articles as soon as they became ready. In October 2008 PLoS ONE came out of "beta". Also in September 2009, as part of its "Article-Level Metrics" program, PLoS ONE made the full online usage data for every published article (HTML page views, PDF, and XML downloads) publicly available.

Publisher
Public Library of Science
History
2006--present
Website
http://www.plosone.org/
Impact factor
4.411 (2010)
Some content from Wikipedia, licensed under CC BY-SA

Engineering

Land use matters as communities cut carbon emissions

With no-wind-turbine signs on roadsides next to cornfields, it's hardly surprising that land use is a thorny issue for renewables. But how much land do different zero-carbon technologies really use?

Robotics

Dog-human bonds could guide development of social robots

A new study highlights specific dog behaviors that dog owners perceive as important for bonding with their pets. Katie Riddoch of the University of Glasgow, Scotland, and colleagues present these findings in the open-access ...

Robotics

A robot that draws circuits with conductive ink to survive

Recent technological advancements have paved the way for the creation of increasingly sophisticated robotic systems designed to autonomously complete missions in different familiar and unfamiliar environments. Robots meant ...

Machine learning & AI

Breaking AIs to make them better

Today's artificial intelligence systems used for image recognition are incredibly powerful with massive potential for commercial applications. Nonetheless, current artificial neural networks—the deep learning algorithms ...

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