SGED-TCD is a lag-resolved causal discovery framework that uses structural gating and perturbation-effect alignment to infer interpretable weighted causal networks from complex time series, shown on heat-pollution extremes in China.
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Simulations across ten scenarios yield duty cycles of technological activity from 0.38 to 1.00, with resource depletion rate and post-collapse recovery fraction as the dominant levers shaping persistence and effective detectability.
Multi-platform remote sensing and modeling document the arrival and altitude-dependent properties of intercontinental smoke from 2017 Pacific Northwest wildfires over Spain.
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Structural Gating and Effect-aligned Lag-resolved Temporal Causal Discovery Framework with Application to Heat-Pollution Extremes
SGED-TCD is a lag-resolved causal discovery framework that uses structural gating and perturbation-effect alignment to infer interpretable weighted causal networks from complex time series, shown on heat-pollution extremes in China.
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Projections of Earth's Technosphere: Civilization Collapse-Recovery Dynamics and Detectability
Simulations across ten scenarios yield duty cycles of technological activity from 0.38 to 1.00, with resource depletion rate and post-collapse recovery fraction as the dominant levers shaping persistence and effective detectability.
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Ground/space, passive/active remote sensing observations coupled with particle dispersion modelling to understand the inter-continental transport of wildfire smoke plumes
Multi-platform remote sensing and modeling document the arrival and altitude-dependent properties of intercontinental smoke from 2017 Pacific Northwest wildfires over Spain.