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Assessing regulatory fairness through machine learning

March 08, 2021

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Applying machine learning to a U.S. Environmental Protection Agency initiative, researchers reveal how key design elements determine what communities bear the burden of pollution. The approach could help ensure fairness and accountability in machine learning used by government regulators.

from Top Technology News -- ScienceDaily https://ift.tt/30onVyN

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Scientists found a way to cool quantum computers using noise

Quantum computers need extreme cold to work, but the very systems that keep them cold also create noise that can destroy fragile quantum information. Scientists in Sweden have now flipped that problem on its head by building a tiny quantum refrigerator that actually uses noise to drive cooling instead of fighting it. By carefully steering heat at unimaginably small scales, the device can act as a refrigerator, heat engine, or energy amplifier inside quantum circuits. from Top Technology News -- ScienceDaily https://ift.tt/fJjN3FO

Nearly half of drivers killed in crashes had THC in their blood

Over 40% of fatal crash victims had THC levels far above legal limits, showing cannabis use before driving remains widespread. The rate didn’t drop after legalization, suggesting policy changes haven’t altered risky habits. Experts warn that the lack of public awareness around marijuana’s dangers behind the wheel is putting lives at risk. from All Top News -- ScienceDaily https://ift.tt/ICbyWJ8

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A research team has developed a liquid metal-based electronic logic device that mimics the intelligent prey-capture mechanism of Venus flytraps. Exhibiting memory and counting properties, the device can intelligently respond to various stimulus sequences without the need for additional electronic components. The intelligent strategies and logic mechanisms in the device provide a fresh perspective on understanding 'intelligence' in nature and offer inspiration for the development of 'embodied intelligence'. from Top Technology News -- ScienceDaily https://ift.tt/tQDMcrC

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Assessing regulatory fairness through machine learning

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