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Fuzzy Logic is a good model for the human ability to compute words. It is based on the theory of fuzzy set. A fuzzy set is different from a classical set because it breaks the Law of the Excluded Middle. In fact, an item may belong to a fuzzy set and its complement at the same time and with the same or different degree of membership. The degree of membership of an item in a fuzzy set can be any real number included between 0 and 1. This property enables us to deal with all those statements of which truths are a matter of degree. Fuzzy logic plays a relevant role in the field of Artificial Intelligence because it enables decision-making in complex situations, where there are many intertwined variables involved. Traditionally, fuzzy logic is implemented through software on a computer or, even better, through analog electronic circuits. Recently, the idea of using molecules and chemical reactions to process fuzzy logic has been promoted. In fact, the molecular word is fuzzy in its essence. The overlapping of quantum states, on the one hand, and the conformational heterogeneity of large molecules, on the other, enable context-specific functions to emerge in response to changing environmental conditions. Moreover, analog input–output relationships, involving not only electrical but also other physical and chemical variables can be exploited to build fuzzy logic systems. The development of “fuzzy chemical systems” is tracing a new path in the field of artificial intelligence. This new path shows that artificially intelligent systems can be implemented not only through software and electronic circuits but also through solutions of properly chosen chemical compounds. The design of chemical artificial intelligent systems and chemical robots promises to have a significant impact on science, medicine, economy, security, and wellbeing. Therefore, it is my great pleasure to announce a Special Issue of Molecules entitled “The Fuzziness in Molecular, Supramolecular, and Systems Chemistry.” All researchers who experience the Fuzziness of the molecular world or use Fuzzy logic to understand Chemical Complex Systems will be interested in this book.

Research & information: general --- Biology, life sciences --- fuzzy logic --- complexity --- chemical artificial intelligence --- human nervous system --- fuzzy proteins --- conformations --- photochromic compounds --- qubit --- protein dynamics --- conformational heterogeneity --- promiscuity --- fuzzy complexes --- higher-order structures --- protein evolution --- fuzzy set theory --- artificial intelligence --- GCN4 mimetic --- peptides-DNA --- E:Z photoisomerization --- conformational fuzziness --- photoelectrochemistry --- wide bandgap semiconductor --- artificial neuron --- in materio computing --- neuromorphic computing --- intrinsically disordered protein --- intrinsically disordered protein region --- liquid-liquid phase transition --- protein-protein interaction --- protein-nucleic acid interaction --- proteinaceous membrane-less organelle --- fuzzy complex. --- d-TST --- activation energy --- Transitivity plot --- solution kinetic --- Maxwell-Boltzmann path --- Euler's formula for the exponential --- activation --- transitivity --- transport phenomena --- moonlighting proteins --- intrinsically disordered proteins --- metamorphic proteins --- morpheeins --- fuzzy logic --- complexity --- chemical artificial intelligence --- human nervous system --- fuzzy proteins --- conformations --- photochromic compounds --- qubit --- protein dynamics --- conformational heterogeneity --- promiscuity --- fuzzy complexes --- higher-order structures --- protein evolution --- fuzzy set theory --- artificial intelligence --- GCN4 mimetic --- peptides-DNA --- E:Z photoisomerization --- conformational fuzziness --- photoelectrochemistry --- wide bandgap semiconductor --- artificial neuron --- in materio computing --- neuromorphic computing --- intrinsically disordered protein --- intrinsically disordered protein region --- liquid-liquid phase transition --- protein-protein interaction --- protein-nucleic acid interaction --- proteinaceous membrane-less organelle --- fuzzy complex. --- d-TST --- activation energy --- Transitivity plot --- solution kinetic --- Maxwell-Boltzmann path --- Euler's formula for the exponential --- activation --- transitivity --- transport phenomena --- moonlighting proteins --- intrinsically disordered proteins --- metamorphic proteins --- morpheeins

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Fuzzy Logic is a good model for the human ability to compute words. It is based on the theory of fuzzy set. A fuzzy set is different from a classical set because it breaks the Law of the Excluded Middle. In fact, an item may belong to a fuzzy set and its complement at the same time and with the same or different degree of membership. The degree of membership of an item in a fuzzy set can be any real number included between 0 and 1. This property enables us to deal with all those statements of which truths are a matter of degree. Fuzzy logic plays a relevant role in the field of Artificial Intelligence because it enables decision-making in complex situations, where there are many intertwined variables involved. Traditionally, fuzzy logic is implemented through software on a computer or, even better, through analog electronic circuits. Recently, the idea of using molecules and chemical reactions to process fuzzy logic has been promoted. In fact, the molecular word is fuzzy in its essence. The overlapping of quantum states, on the one hand, and the conformational heterogeneity of large molecules, on the other, enable context-specific functions to emerge in response to changing environmental conditions. Moreover, analog input–output relationships, involving not only electrical but also other physical and chemical variables can be exploited to build fuzzy logic systems. The development of “fuzzy chemical systems” is tracing a new path in the field of artificial intelligence. This new path shows that artificially intelligent systems can be implemented not only through software and electronic circuits but also through solutions of properly chosen chemical compounds. The design of chemical artificial intelligent systems and chemical robots promises to have a significant impact on science, medicine, economy, security, and wellbeing. Therefore, it is my great pleasure to announce a Special Issue of Molecules entitled “The Fuzziness in Molecular, Supramolecular, and Systems Chemistry.” All researchers who experience the Fuzziness of the molecular world or use Fuzzy logic to understand Chemical Complex Systems will be interested in this book.

Research & information: general --- Biology, life sciences --- fuzzy logic --- complexity --- chemical artificial intelligence --- human nervous system --- fuzzy proteins --- conformations --- photochromic compounds --- qubit --- protein dynamics --- conformational heterogeneity --- promiscuity --- fuzzy complexes --- higher-order structures --- protein evolution --- fuzzy set theory --- artificial intelligence --- GCN4 mimetic --- peptides–DNA --- E:Z photoisomerization --- conformational fuzziness --- photoelectrochemistry --- wide bandgap semiconductor --- artificial neuron --- in materio computing --- neuromorphic computing --- intrinsically disordered protein --- intrinsically disordered protein region --- liquid–liquid phase transition --- protein–protein interaction --- protein–nucleic acid interaction --- proteinaceous membrane-less organelle --- fuzzy complex. --- d-TST --- activation energy --- Transitivity plot --- solution kinetic --- Maxwell–Boltzmann path --- Euler’s formula for the exponential --- activation --- transitivity --- transport phenomena --- moonlighting proteins --- intrinsically disordered proteins --- metamorphic proteins --- morpheeins --- n/a --- peptides-DNA --- liquid-liquid phase transition --- protein-protein interaction --- protein-nucleic acid interaction --- Maxwell-Boltzmann path --- Euler's formula for the exponential

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Some in the social sciences argue that the same logic applies to both qualitative and quantitative methods. In A Tale of Two Cultures, Gary Goertz and James Mahoney demonstrate that these two paradigms constitute different cultures, each internally coherent yet marked by contrasting norms, practices, and toolkits. They identify and discuss major differences between these two traditions that touch nearly every aspect of social science research, including design, goals, causal effects and models, concepts and measurement, data analysis, and case selection. Although focused on the differences between qualitative and quantitative research, Goertz and Mahoney also seek to promote toleration, exchange, and learning by enabling scholars to think beyond their own culture and see an alternative scientific worldview. This book is written in an easily accessible style and features a host of real-world examples to illustrate methodological points.

Social sciences --- Political sociology --- Political science --- Mass political behavior --- Political behavior --- Sociology --- Administration --- Civil government --- Commonwealth, The --- Government --- Political theory --- Political thought --- Politics --- Science, Political --- State, The --- Research --- Methodology. --- Sociological aspects --- 2 x 2 tables. --- David Hume. --- Fundamental Principle of Variable Transformation. --- Fundamental Problem of Causal Inference. --- Fundamental Tradeoffs. --- Hooke's law. --- Principle of Conceptual Opposites. --- Principle of Conceptual Overlap. --- Principle of Unimportant Variation. --- additive-linear causal model. --- aggregation technique. --- asymmetry. --- case selection. --- case studies. --- cases. --- categories. --- causal complexity. --- causal effects. --- causal heterogeneity. --- causal inference. --- causal mechanism. --- causal model. --- causal models. --- causal-process observations. --- causality. --- causation. --- cause. --- causes-of-effects approach. --- characteristics. --- concepts. --- conceptualization. --- constant conjunction definition. --- control variables. --- counterfactual analysis. --- counterfactual definition. --- counterfactuals. --- cross-case analysis. --- data analysis. --- data transformations. --- data-set observations. --- definitions. --- dependent variable. --- effects-of-causes approach. --- empirical testing. --- equifinality. --- error. --- experiments. --- fuzziness. --- fuzzy-set analysis. --- fuzzy-set transformations. --- generalization. --- hypothesis testing. --- indicators. --- individual case analysis. --- individual cases. --- inferential statistics. --- logging. --- logic. --- meaning retention. --- measurement. --- membership functions. --- methodological pluralism. --- minimum rewrite rule. --- mixed-method research. --- multimethod research. --- multiple causation. --- natural language. --- necessary condition. --- nonoccurrence. --- occurrence. --- opposites. --- perfect predictors. --- political science. --- probability theory. --- process tracing. --- qualitative research. --- quantitative research. --- regression. --- scale types. --- scope conditions. --- semantic transformations. --- semantics. --- set theory. --- set-theoretic causal model. --- set-theoretic generalization. --- social science research. --- social sciences. --- sociology. --- standardization. --- static causal asymmetry. --- statistical analysis. --- statistical method. --- statistical model. --- statistics. --- sufficient condition. --- symmetry. --- translation problems. --- typologies. --- variable transformations. --- within-case analysis. --- within-model responses.