Choosing between human and algorithmic decision-makers
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Updates every hour. Last Updated: 11-May-2025 06:09 ET (11-May-2025 10:09 GMT/UTC)
- Mathematicians led by the University of Leicester have applied statistical mechanics to climate change detection and attribution for first time
- They have shown how to separate the ‘signal’ of human-made climate change from the ‘noise’ of natural climate fluctuations
- Allows a dramatic improvement in the ability to detect climate change and early warnings of climatic tipping points
Fluorescence is a well-known phenomenon with many practical applications that has been studied for decades. Despite this, a commonly used mathematical formalism to describe how it evolves over time does not make physical sense under certain conditions, as researchers from the Institute of Physical Chemistry, Polish Academy of Sciences have recently discovered. Namely, they showed that a mathematical tool that can be safely used in solids, where molecules are practically immobile, cannot always be used in liquids, where they can move freely. If applied incorrectly, this widely used approach can lead to erroneous interpretations of experimental data and wrong conclusions. This is what their recent paper in the Journal of Chemical Physics warns us about.
A new paper in the Journal of Public Health finds that household income in early childhood is a stronger and more consistent predictor for several major health-related problems for 17-year-olds than growing up in a poor neighborhood. The neighborhood was a slightly stronger predictor for obesity only.