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"Next Big Future" - 3 new articles
- Nuclear power has prevented 1.84 million air pollution deaths and could save millions more in the coming decades
- Artificial intelligence related Sparse coding on D-Wave quantum computer hardware
- By 2015 the Chinese yuan will be the number three currency in the world after the US dollar and the Euro
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Nuclear power has prevented 1.84 million air pollution deaths and could save millions more in the coming decadesUsing nuclear power in place of fossil-fuel energy sources, such as coal, has prevented some 1.84 million air pollution-related deaths globally and could save millions of more lives in coming decades, concludes a study. The researchers also find that nuclear energy prevents emissions of huge quantities of greenhouse gases. These estimates help make the case that policymakers should continue to rely on and expand nuclear power in place of fossil fuels to mitigate climate change.
Environmental Science and Technology Journal - Prevented mortality and greenhouse gas emissions from historical and projected nuclear power by Pushker A. Kharecha and James E Hansen. Hansen is a famous NASA scientist who is well known for his position to stop climate change.
 Nextbigfuture has a lot of coverage of air pollution and deaths per terawatt hour by energy source Deaths per twh by energy source in 2012. A Nextbigfuture article from 2011. A look at lowering the deaths per terawatt hour by reducing pollution and making energy safer. A review of peer reviewed studies of air pollution deaths. Several dozen other articles going back to 2008 Read more »          
     Artificial intelligence related Sparse coding on D-Wave quantum computer hardwareSparse coding provides a class of algorithms for finding succinct representations of stimuli; given only unlabeled input data, it discovers basis functions that capture higher-level features in the data. However, finding sparse codes remains a very difficult computational problem. In this paper, we present efficient sparse coding algorithms that are based on iteratively solving two convex optimization problems: an L1-regularized least squares problem and an L2-constrained least squares problem. We propose novel algorithms to solve both of these optimization problems. Our algorithms result in a significant speedup for sparse coding, allowing us to learn larger sparse codes than possible with previously described algorithms. We apply these algorithms to natural images and demonstrate that the inferred sparse codes exhibit end-stopping and non-classical receptive field surround suppression and, therefore, may provide a partial explanation for these two phenomena in V1 neurons.
Sparse coding is a very interesting idea that Dwave Systems been experimenting with on their adiabatic quantum computer. Sparse coding is a way to find ‘maximally repeating patterns’ in data, and use these as a basis for representing that data. Sparse coding is probably related to how human perception and cognition functions. Unsupervised Feature Learning and Deep Learning 
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 By 2015 the Chinese yuan will be the number three currency in the world after the US dollar and the EuroThere are several recent forecast / predictions for the Chinese yuan by noted economists.
* By 2015, a third of China’s cross-border trade will be settled in yuan, making the yuan one of the three most-used in global trade along with the dollar and euro, HSBC forecast in a report this month * The Chinese yuan will appreciate 2.1 percent to 6.1 per dollar this year * “I would expect China to increasingly move towards a managed float with more flexibility,” Irene Cheung, a foreign- exchange strategist at Australia & New Zealand Banking Group in Singapore, said by telephone today. “Basically convertible is possible in five years, but it might not be 100 percent convertible.” London is racing against Paris and Zurich to become the center for yuan trading in Europe as China seeks to take its currency global. Read more »     
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