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We present a mathematical framework (referred to as Context-driven Actualization of Potential, or CAP) for describing how entities change over time under the influence of a context. The approach facilitates comparison of change of state of entities studied in different disciplines. Processes are seen to differ according to the degree of nondeterminism, and the degree to which they are sensitive to, internalize, and depend upon a particular context. Our analysis suggests that the dynamical evolution of a quantum entity described by the Schrodinger equation is not fundamentally different from change provoked by a measurement often referred to as collapse, but a limiting case, with only one way to collapse. The biological transition to coded replication is seen as a means of preserving structure in the fact of context-driven change, and sextual replication as a means of increasing potentiality thus enhancing diversity through interaction with context. The framework sheds light on concepts like selection and fitness, reveals how exceptional Darwinian evolution is as a means of change of state, and clarifies in what sense culture, and the creative process underlying it, are Darwinian.
The body is home to a diverse microbiota, mainly in the gut. Resistant bacteria are selected for by antibiotic treatments, and once resistance becomes widespread in a population of hosts, antibiotics become useless. Here, we develop a multiscale mode
MHD-based global space weather models have mostly been developed and maintained at academic institutions. While the free spirit approach of academia enables the rapid emergence and testing of new ideas and methods, the lack of long-term stability and
A hidden variables model complying with the simplest form of Local Realism was recently introduced, which reproduces Quantum Mechanics predictions for an even ideally perfect Bells experiment. This is possible thanks to the use of a non-Boolean vecto
In epidemiological modelling, the instantaneous reproduction number, $R_t$, is important to understand the transmission dynamics of infectious diseases. Current $R_t$ estimates often suffer from problems such as lagging, averaging and uncertainties d
We study the coevolutionary dynamics of the diversity of phenotype expression and the evolution of cooperation in the Prisoners Dilemma game. Rather than pre-assigning zero-or-one interaction rate, we diversify the rate of interaction by associating