4,556 research outputs found

    Cyclic proof systems for modal fixpoint logics

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    This thesis is about cyclic and ill-founded proof systems for modal fixpoint logics, with and without explicit fixpoint quantifiers.Cyclic and ill-founded proof-theory allow proofs with infinite branches or paths, as long as they satisfy some correctness conditions ensuring the validity of the conclusion. In this dissertation we design a few cyclic and ill-founded systems: a cyclic one for the weak Grzegorczyk modal logic K4Grz, based on our explanation of the phenomenon of cyclic companionship; and ill-founded and cyclic ones for the full computation tree logic CTL* and the intuitionistic linear-time temporal logic iLTL. All systems are cut-free, and the cyclic ones for K4Grz and iLTL have fully finitary correctness conditions.Lastly, we use a cyclic system for the modal mu-calculus to obtain a proof of the uniform interpolation property for the logic which differs from the original, automata-based one

    Fuzzy Natural Logic in IFSA-EUSFLAT 2021

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    The present book contains five papers accepted and published in the Special Issue, “Fuzzy Natural Logic in IFSA-EUSFLAT 2021”, of the journal Mathematics (MDPI). These papers are extended versions of the contributions presented in the conference “The 19th World Congress of the International Fuzzy Systems Association and the 12th Conference of the European Society for Fuzzy Logic and Technology jointly with the AGOP, IJCRS, and FQAS conferences”, which took place in Bratislava (Slovakia) from September 19 to September 24, 2021. Fuzzy Natural Logic (FNL) is a system of mathematical fuzzy logic theories that enables us to model natural language terms and rules while accounting for their inherent vagueness and allows us to reason and argue using the tools developed in them. FNL includes, among others, the theory of evaluative linguistic expressions (e.g., small, very large, etc.), the theory of fuzzy and intermediate quantifiers (e.g., most, few, many, etc.), and the theory of fuzzy/linguistic IF–THEN rules and logical inference. The papers in this Special Issue use the various aspects and concepts of FNL mentioned above and apply them to a wide range of problems both theoretically and practically oriented. This book will be of interest for researchers working in the areas of fuzzy logic, applied linguistics, generalized quantifiers, and their applications

    Revisiting Language Support for Generic Programming: When Genericity Is a Core Design Goal

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    ContextGeneric programming, as defined by Stepanov, is a methodology for writing efficient and reusable algorithms by considering only the required properties of their underlying data types and operations. Generic programming has proven to be an effective means of constructing libraries of reusable software components in languages that support it. Generics-related language design choices play a major role in how conducive generic programming is in practice.InquirySeveral mainstream programming languages (e.g. Java and C++) were first created without generics; features to support generic programming were added later, gradually. Much of the existing literature on supporting generic programming focuses thus on retrofitting generic programming into existing languages and identifying related implementation challenges. Is the programming experience significantly better, or different when programming with a language designed for generic programming without limitations from prior language design choices?ApproachWe examine Magnolia, a language designed to embody generic programming. Magnolia is representative of an approach to language design rooted in algebraic specifications. We repeat a well-known experiment, where we put Magnolia’s generic programming facilities under scrutiny by implementing a subset of the Boost Graph Library, and reflect on our development experience.KnowledgeWe discover that the idioms identified as key features for supporting Stepanov-style generic programming in the previous studies and work on the topic do not tell a full story. We clarify which of them are more of a means to an end, rather than fundamental features for supporting generic programming. Based on the development experience with Magnolia, we identify variadics as an additional key feature for generic programming and point out limitations and challenges of genericity by property.GroundingOur work uses a well-known framework for evaluating the generic programming facilities of a language from the literature to evaluate the algebraic approach through Magnolia, and we draw comparisons with well-known programming languages.ImportanceThis work gives a fresh perspective on generic programming, and clarifies what are fundamental language properties and their trade-offs when considering supporting Stepanov-style generic programming. The understanding of how to set the ground for generic programming will inform future language design.</p

    Theologische Zugänge zu Technik und Künstlicher Intelligenz

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    The publication of this work was supported by the Open Access Publication Fund of Humboldt-Universität zu Berlin.Technik und Künstliche Intelligenz gehören zu den brisanten Themen der gegenwärtigen Theologie. Wie kann Theologie zu Technik und KI beitragen? Der Technikdiskurs ist aufgeladen mit religiösen Motiven, und Technologien wie Roboter fordern die Theologie, z. B. das Menschenbild, die Ethik und die religiöse Praxis, neu heraus. Der Sammelband erforscht aus theologischer Perspektive die drängenden Themen unserer Zeit. Dazu begibt sich die Theologie in Dialog mit den Technikwissenschaften. Untersucht werden die Veränderungen des Menschenbildes durch Roboter, Religiöse Roboter, Optimierung des Körpers, medizinische Technologien, Autoregulative Waffensysteme und wie die Theologie durch die Technologisierung transformiert wird. Aus interdisziplinärer Perspektive werden neue Forschungsergebnisse aus dem internationalen Raum vorgestellt und neue Wege beschritten

    Complexity Science in Human Change

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    This reprint encompasses fourteen contributions that offer avenues towards a better understanding of complex systems in human behavior. The phenomena studied here are generally pattern formation processes that originate in social interaction and psychotherapy. Several accounts are also given of the coordination in body movements and in physiological, neuronal and linguistic processes. A common denominator of such pattern formation is that complexity and entropy of the respective systems become reduced spontaneously, which is the hallmark of self-organization. The various methodological approaches of how to model such processes are presented in some detail. Results from the various methods are systematically compared and discussed. Among these approaches are algorithms for the quantification of synchrony by cross-correlational statistics, surrogate control procedures, recurrence mapping and network models.This volume offers an informative and sophisticated resource for scholars of human change, and as well for students at advanced levels, from graduate to post-doctoral. The reprint is multidisciplinary in nature, binding together the fields of medicine, psychology, physics, and neuroscience

    Procedural Constraint-based Generation for Game Development

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    Natural type inference

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    Recently, dynamic language users have started to recognize the value of types in their code. To fulfil this need, many popular dynamic languages have adopted extensions that support type annotations. A prominent example is that of TypeScript which offers a module system, classes, interfaces, and an optional type system on top of JavaScript. However, providing usable (not too verbose, or complex) types via traditional type inference is more challenging in optional type systems. Motivated by this, we redefine the goal of type inference for optionally typed languages as: infer the maximally natural and sound type, instead of the most general one. By the maximally natural and sound, we refer to a type that (1) is derivable in the type system, and (2) maximally reflects the intention of the programmer with respect to a learnt model. We formally devise a type inference problem that aids the inference of the maximally natural type. Towards this goal, our problem asks to combine information derived from two sources: (1) from algorithmic type systems using deductive logic-based techniques; and (2) from the source code text using inductive machine learning techniques. To tackle our formulated problem, we develop two frameworks that combine the two sources of information using mathematical optimization. In the first framework, we formulate the inference problem as a problem in numerical optimization. In the second framework, we map the inference problem into popular problems in discrete optimization: maximum satisfiability (MaxSAT) and Integer Linear Programming (ILP). Both frameworks are built to be consistent with information derived from the different sources. Moreover, through formal proofs, we validate the soundness and completeness of the developed framework for a core lambda-calculus with named types. To assess the efficacy of the developed frameworks, we implement them in a tool named Optyper that realizes natural type inference for TypeScript. We evaluate Optyperon TypeSript programs obtained from real world projects. By evaluating our theoretical frameworks we show that, in practice, the combination of logical and natural constraints yields a large improvement in performance over either kind of information individually. Further, we demonstrate that our frameworks out-perform state-of-the-art techniques in type inference to produce natural and sound types

    Specificity of the innate immune responses to different classes of non-tuberculous mycobacteria

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    Mycobacterium avium is the most common nontuberculous mycobacterium (NTM) species causing infectious disease. Here, we characterized a M. avium infection model in zebrafish larvae, and compared it to M. marinum infection, a model of tuberculosis. M. avium bacteria are efficiently phagocytosed and frequently induce granuloma-like structures in zebrafish larvae. Although macrophages can respond to both mycobacterial infections, their migration speed is faster in infections caused by M. marinum. Tlr2 is conservatively involved in most aspects of the defense against both mycobacterial infections. However, Tlr2 has a function in the migration speed of macrophages and neutrophils to infection sites with M. marinum that is not observed with M. avium. Using RNAseq analysis, we found a distinct transcriptome response in cytokine-cytokine receptor interaction for M. avium and M. marinum infection. In addition, we found differences in gene expression in metabolic pathways, phagosome formation, matrix remodeling, and apoptosis in response to these mycobacterial infections. In conclusion, we characterized a new M. avium infection model in zebrafish that can be further used in studying pathological mechanisms for NTM-caused diseases

    2023-2024 Undergraduate Catalog

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    2023-2024 undergraduate catalog for Morehead State University
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