G-CPT Symmetry of Quantum Emergence and Submergence -- An Information Conservational Multiagent Cellular Automata Unification of CPT Symmetry and CP Violation for Equilibrium-Based Many-World Causal Analysis of Quantum Coherence and Decoherence

An equilibrium-based YinYang bipolar dynamic Generalization of CPT (G -CPT) symmetry is introduced based on energy/information conservational quantum emergence-submergence. As a bottleneck of quantum computing, quantum decoherence or collapse has been plaguing quantum mechanics for decades. It is suggested that the crux of the problem can trace its origin back to the incompleteness of CPT symmetry due to the lack of holistic representation for equilibrium-based bipolar coexistence. In this work, the notion of quantum emergence-submergence is coined as two opposite processes with bipolar energy/information conservation. The new notion leads to G-CPT symmetry supported by a Bipolar Quantum Cellular Automata (BQCA) interpretation of quantum mechanics. It is shown that the new interpretation further leads to the unification of electromagnetic particle- antiparticle bipolarity and gravitational action-reaction bipolarity as well as CPT symmetry and CP violation into a philosophically, geometrically and logically different quantum gravity theory. On one hand, G -CPT symmetry enables a Bipolar Quantum Agent (BQA) to emerge as a bipolar quantum superposition or entanglement coupled to a globally coherent BQCA; on the other hand, G -CP violation supports a causal theory of BQA submergence or decoupling from the global coherence. In turn, BQAs can submerge from one world but emerge in another within YinYang bipolar quantum geometry. It is suggested t hat all logical, physical, social, biological and mental worlds are bipolar quantum entangled under G -CPT symmetry. It is contended that G -CPT symmetry constitutes an analytical paradigm of quantum mechanics and quantum gravity— a fundamental departure from “what goes around comes around ”. The new paradigm leads to a number of predictions and challenges

Categorical Ontology of Complex Systems, Meta-Systems and Theory of Levels: The Emergence of Life, Human Consciousness and Society

Single cell interactomics in simpler organisms, as well as somatic cell interactomics in multicellular organisms, involve biomolecular interactions in complex signalling pathways that were recently represented in modular terms by quantum automata with ‘reversible behavior’ representing normal cell cycling and division. Other implications of such quantum automata, modular modeling of signaling pathways and cell differentiation during development are in the fields of neural plasticity and brain development leading to quantum-weave dynamic patterns and specific molecular processes underlying extensive memory, learning, anticipation mechanisms and the emergence of human consciousness during the early brain development in children. Cell interactomics is here represented for the first time as a mixture of ‘classical’ states that determine molecular dynamics subject to Boltzmann statistics and ‘steady-state’, metabolic (multi-stable) manifolds, together with ‘configuration’ spaces of metastable quantum states emerging from complex quantum dynamics of interacting networks of biomolecules, such as proteins and nucleic acids that are now collectively defined as quantum interactomics. On the other hand, the time dependent evolution over several generations of cancer cells --that are generally known to undergo frequent and extensive genetic mutations and, indeed, suffer genomic transformations at the chromosome level (such as extensive chromosomal aberrations found in many colon cancers)-- cannot be correctly represented in the ‘standard’ terms of quantum automaton modules, as the normal somatic cells can. This significant difference at the cancer cell genomic level is therefore reflected in major changes in cancer cell interactomics often from one cancer cell ‘cycle’ to the next, and thus it requires substantial changes in the modeling strategies, mathematical tools and experimental designs aimed at understanding cancer mechanisms. Novel solutions to this important problem in carcinogenesis are proposed and experimental validation procedures are suggested. From a medical research and clinical standpoint, this approach has important consequences for addressing and preventing the development of cancer resistance to medical therapy in ongoing clinical trials involving stage III cancer patients, as well as improving the designs of future clinical trials for cancer treatments.\ud \ud \ud KEYWORDS: Emergence of Life and Human Consciousness;\ud Proteomics; Artificial Intelligence; Complex Systems Dynamics; Quantum Automata models and Quantum Interactomics; quantum-weave dynamic patterns underlying human consciousness; specific molecular processes underlying extensive memory, learning, anticipation mechanisms and human consciousness; emergence of human consciousness during the early brain development in children; Cancer cell ‘cycling’; interacting networks of proteins and nucleic acids; genetic mutations and chromosomal aberrations in cancers, such as colon cancer; development of cancer resistance to therapy; ongoing clinical trials involving stage III cancer patients’ possible improvements of the designs for future clinical trials and cancer treatments. \ud \u

Epistemic Communities in Urban Self-organization: A Systematic Review and Assessment

The application of the concept of self-organization has grown over time in the field of urban planning, but with various interpretations. This article presents a systematic review that aims to uncover whether different uses of self-organization are tied to epistemic communities. Through coding and bibliographical analysis, it became apparent that there are two epistemic communities that emphasize different conceptualizations of self-organization. They investigate different issues, use different methods, a

Formal Models for Biological Systems

In the last thirty years, formal models have been thoroughly employed in the realm of biological systems for many reasons: (i) preventing those ambiguities that may arise when informal notations are used for system description, (ii) supporting the development of simulators, (iii) supporting the development of tools, such as model checkers, allowing for verifying whether a system satisfies a given behavioural property, (iv) offering several instruments allowing for comparing the behaviour of different systems. The work in this thesis can be divided into two contributions concerning formal models for biological systems. The first contribution is related to the study of the robustness of biochemical networks. In particular, we take inspiration from the notion of alpha-robustness, which, intuitively, verifies how by varying the initial concentration of some species, called conventionally the input species, the concentration of other species of interest, called the output species, varies at steady state. Robustness in our sense captures random effects and temporary effects that are typical of the stochastic model. We will employ: (i) the process calculi approach for specifying systems of interest, (ii) the semantic model of evolution sequences, which, intuitively, model the behaviour of a system as the sequence of probability measures over the attainable configurations, (iii) a formal notion of robustness, defined on the semantic model, and (iv) an algorithm allowing us to estimate the robustness of a system starting from its specification. We validate our approach on three case studies EnvZ/OmpR Osmoregulatory Signaling System in Escherichia Coli, which is an example of the regulatory network, the mechanism of Bacterial Chemotaxis of Escherichia Coli, and an abstract chemical reaction network, called Enzyme Activity at Saturation. We have provided a Python implementation available at https://github.com/dmanicardi/spebnr. Our second contribution is showing how the features of CospanSpan(Graph) can be exploited in modelling biological systems. CospanSpan(Graph) offers an algebraic approach for the compositional description of variable topology networks that has been only partially exploited so far for the formalisation of that kind of systems. In particular, we provide a simplified model of a human heart and a model of a dual-chamber pacemaker that can interact with the model of the heart. Then, we model a gene regulatory network, namely the Lac Operon of Escherichia Coli.In the last thirty years, formal models have been thoroughly employed in the realm of biological systems for many reasons: (i) preventing those ambiguities that may arise when informal notations are used for system description, (ii) supporting the development of simulators, (iii) supporting the development of tools, such as model checkers, allowing for verifying whether a system satisfies a given behavioural property, (iv) offering several instruments allowing for comparing the behaviour of different systems. The work in this thesis can be divided into two contributions concerning formal models for biological systems. The first contribution is related to the study of the robustness of biochemical networks. In particular, we take inspiration from the notion of alpha-robustness, which, intuitively, verifies how by varying the initial concentration of some species, called conventionally the input species, the concentration of other species of interest, called the output species, varies at steady state. Robustness in our sense captures random effects and temporary effects that are typical of the stochastic model. We will employ: (i) the process calculi approach for specifying systems of interest, (ii) the semantic model of evolution sequences, which, intuitively, model the behaviour of a system as the sequence of probability measures over the attainable configurations, (iii) a formal notion of robustness, defined on the semantic model, and (iv) an algorithm allowing us to estimate the robustness of a system starting from its specification. We validate our approach on three case studies EnvZ/OmpR Osmoregulatory Signaling System in Escherichia Coli, which is an example of the regulatory network, the mechanism of Bacterial Chemotaxis of Escherichia Coli, and an abstract chemical reaction network, called Enzyme Activity at Saturation. We have provided a Python implementation available at https://github.com/dmanicardi/spebnr. Our second contribution is showing how the features of CospanSpan(Graph) can be exploited in modelling biological systems. CospanSpan(Graph) offers an algebraic approach for the compositional description of variable topology networks that has been only partially exploited so far for the formalisation of that kind of systems. In particular, we provide a simplified model of a human heart and a model of a dual-chamber pacemaker that can interact with the model of the heart. Then, we model a gene regulatory network, namely the Lac Operon of Escherichia Coli

Foundations of Software Science and Computation Structures

This open access book constitutes the proceedings of the 23rd International Conference on Foundations of Software Science and Computational Structures, FOSSACS 2020, which took place in Dublin, Ireland, in April 2020, and was held as Part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2020. The 31 regular papers presented in this volume were carefully reviewed and selected from 98 submissions. The papers cover topics such as categorical models and logics; language theory, automata, and games; modal, spatial, and temporal logics; type theory and proof theory; concurrency theory and process calculi; rewriting theory; semantics of programming languages; program analysis, correctness, transformation, and verification; logics of programming; software specification and refinement; models of concurrent, reactive, stochastic, distributed, hybrid, and mobile systems; emerging models of computation; logical aspects of computational complexity; models of software security; and logical foundations of data bases.

Logics for AI and Law: Joint Proceedings of the Third International Workshop on Logics for New-Generation Artificial Intelligence and the International Workshop on Logic, AI and Law, September 8-9 and 11-12, 2023, Hangzhou

This comprehensive volume features the proceedings of the Third International Workshop on Logics for New-Generation Artificial Intelligence and the International Workshop on Logic, AI and Law, held in Hangzhou, China on September 8-9 and 11-12, 2023. The collection offers a diverse range of papers that explore the intersection of logic, artificial intelligence, and law. With contributions from some of the leading experts in the field, this volume provides insights into the latest research and developments in the applications of logic in these areas. It is an essential resource for researchers, practitioners, and students interested in the latest advancements in logic and its applications to artificial intelligence and law