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Following the classical work of Norbert Wiener, Ross Ashby, Ludwig von Bertalanffy and many others, the concept of System has been elaborated in different disciplinary fields, allowing interdisciplinary approaches in areas such as Physics, Biology, Chemistry, Cognitive Science, Economics, Engineering, Social Sciences, Mathematics, Medicine, Artificial Intelligence, and Philosophy. The new challenge of Complexity and Emergence has made the concept of System even more relevant to the study of problems with high contextuality. This Special Issue focuses on the nature of new problems arising from the study and modelling of complexity, their eventual common aspects, properties and approaches—already partially considered by different disciplines—as well as focusing on new, possibly unitary, theoretical frameworks. This Special Issue aims to introduce fresh impetus into systems research when the possible detection and correction of mistakes require the development of new knowledge. This book contains contributions presenting new approaches and results, problems and proposals. The context is an interdisciplinary framework dealing, in order, with electronic engineering problems; the problem of the observer; transdisciplinarity; problems of organised complexity; theoretical incompleteness; design of digital systems in a user-centred way; reaction networks as a framework for systems modelling; emergence of a stable system in reaction networks; emergence at the fundamental systems level; behavioural realization of memoryless functions.

Uncertainty --- Noise --- Memory Less Functions --- Self-Organisation --- Complexity --- Design --- Meta-Structures --- Scale Invariance --- Organisations --- Quantum-Like Systems --- Emergence --- Observer --- Cybernetic Approach --- Power Laws --- Reaction Networks --- Simulations --- Uniqueness --- Irreversibility --- Systems --- Incompleteness --- Computation --- Non-Linearity --- Coherence

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Investigation of the fractal and scaling properties of disordered systems has recently become a focus of great interest in research. Disordered or amorphous materials, like glasses, polymers, gels, colloids, ceramic superconductors and random alloys or magnets, do not have a homogeneous microscopic structure. The microscopic environment varies randomly from site to site in the system and this randomness adds to the complexity and the richness of the properties of these materials. A particularly challenging aspect of random systems is their dynamical behavior. Relaxation in disordered systems

Order-disorder models --- Scaling laws (Statistical physics) --- Statistical physics --- Ratio and proportion (Statistical physics) --- Scale invariance (Statistical physics) --- Scaling hypothesis (Statistical physics) --- Scaling phenomena (Statistical physics) --- Physical laws --- Ranking and selection (Statistics) --- Coniglio, Antonio, --- Coniglio, A.

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Operational research. Game theory --- Engineering mathematics. --- Mathematical analysis. --- Scaling laws (Statistical physics) --- Ratio and proportion (Statistical physics) --- Scale invariance (Statistical physics) --- Scaling hypothesis (Statistical physics) --- Scaling phenomena (Statistical physics) --- Physical laws --- Ranking and selection (Statistics) --- Statistical physics --- Advanced calculus --- Analysis (Mathematics) --- Algebra --- Engineering --- Engineering analysis --- Mathematical analysis --- Mathematics --- 517.1 Mathematical analysis --- Scaling laws (Statistical physics). --- Engineering mathematics --- 517.1. --- 517.1

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Advances in nonlinear dynamics, especially modern multifractal cascade models, allow us to investigate the weather and climate at unprecedented levels of accuracy. Using new stochastic modelling and data analysis techniques, this book provides an overview of the nonclassical, multifractal statistics. By generalizing the classical turbulence laws, emergent higher-level laws of atmospheric dynamics are obtained and are empirically validated over time-scales of seconds to decades and length-scales of millimetres to the size of the planet. In generalizing the notion of scale, atmospheric complexity is reduced to a manageable scale-invariant hierarchy of processes, thus providing a new perspective for modelling and understanding the atmosphere. This synthesis of state-of-the-art data and nonlinear dynamics is systematically compared with other analyses and global circulation model outputs. This is an important resource for atmospheric science researchers new to multifractal theory and is also valuable for graduate students in atmospheric dynamics and physics, meteorology, oceanography and climatology.

Meteorology --- Atmospheric physics --- Fractals --- Scaling laws (Statistical physics) --- Meteorology. --- Atmospheric physics. --- Fractals. --- Ratio and proportion (Statistical physics) --- Scale invariance (Statistical physics) --- Scaling hypothesis (Statistical physics) --- Scaling phenomena (Statistical physics) --- Physical laws --- Ranking and selection (Statistics) --- Statistical physics --- Fractal geometry --- Fractal sets --- Geometry, Fractal --- Sets, Fractal --- Sets of fractional dimension --- Dimension theory (Topology) --- Aerophysics --- Meteorology, Physical --- Physical meteorology --- Atmospheric science --- Aerology

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Scaling laws (Statistical physics) --- Soil physics --- 551.3 --- 551.3 External geodynamics (exogenous processes) --- External geodynamics (exogenous processes) --- Agricultural physics --- Soil mechanics --- Ratio and proportion (Statistical physics) --- Scale invariance (Statistical physics) --- Scaling hypothesis (Statistical physics) --- Scaling phenomena (Statistical physics) --- Physical laws --- Ranking and selection (Statistics) --- Statistical physics