Universal Causality is a mathematical framework based on higher-order category theory, which generalizes previous approaches based on directed graphs and regular categories. We present a hierarchical framework called UCLA (Universal Causality Layered Architecture), where at the top-most level, causal interventions are modeled as a higher-order category over simplicial sets and objects. Simplicial sets are contravariant functors from the category of ordinal numbers Δ into sets, and whose morphisms are order-preserving injections and surjections over finite ordered sets.
View Article and Find Full Text PDFThe task of proper baseline or continuum removal is common to nearly all types of spectroscopy. Its goal is to remove any portion of a signal that is irrelevant to features of interest while preserving any predictive information. Despite the importance of baseline removal, median or guessed default parameters are commonly employed, often using commercially available software supplied with instruments.
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