Logical Representation Research Articles

Logical qubit implementation for quantum annealing: augmented Lagrangian approach

Solving optimization problems on quantum annealers (QA) usually requires each variable of the problem to be represented by a connected set of qubits called a logical qubit or a chain. Chain weights, in the form of ferromagnetic coupling between the chain qubits, are applied so that the physical qubits in a chain favor taking the same value in low energy samples. Assigning a good chain-strength value is crucial for the ability of QA to solve hard problems, but there are no general methods for computing such a value and, even if an optimal value is found, it may still not be suitable by being too large for accurate annealing results. In this paper, we propose an optimization-based approach for producing suitable logical qubits representations that results in smaller chain weights and show that the resulting optimization problem can be successfully solved using the augmented Lagrangian method. Experiments on the D-Wave Advantage system and the maximum clique problem on random graphs show that our approach outperforms both the default D-Wave method for chain-strength assignment as well as the quadratic penalty method.

The Logic of Posthuman Inquiry: Affirmative Politics, Validity, and Futurities

Empirical research informed by posthumanist philosophy is proliferating in the social sciences. This research takes many forms and is willfully pluralistic and creative in the analytic approaches it takes. The innovation, however, is not entirely free form. Posthumanist scholarship both employs familiar forms of inference and is also forwarding a distinctive array of inferential practices that until now have not been commonly present in mainstream/whitestream social sciences. Attending to the logic of emerging posthumanist empiricism can help clarify the affirmative ethics and politics of posthumanist inquiry. This essay offers that a modal, dialethic, paraconsistent logic of action is more suited to posthumanist inquiry than a classical logic of representation. This logic of action locates validity not with the accuracy of representations, but in the specific character of the futurities enabled and disabled by the ontologically generative action of inquiry. Implications for an axiology of posthumanist empiricism are explored.

Translation, cross-cultural adaptation and evaluation of the Iranian Persian version of student survey on writing nursing care plan.

The objective of this study was to validate the Iranian translation and cross-cultural adaptation of the Student Survey on Writing Nursing Care Plan (SSW-NCP). To provide supporting evidence about the nursing students' skill in planning and documenting nursing care plans based on nursing process, Salvador et al. developed the SSW-NCP to measure the extent to which nursing students are qualified in writing nursing care plans. However, an Iranian version of the SSW-NCP is presently not available. The cross-cultural adaptation and linguistic translation of the SSW-NCP adhered to World Health Organization (WHO) guidelines. The reliability and validity process followed the COSMIN checklist. The survey was well translated to Persian language and culturally adapted through confirming the relevancy, appropriateness and logical representation of all aspects on nursing process by bilingual experts and pre-tested on Persian-speaking nursing students. The Cronbach's Alpha coefficient (α) and test-retest stability assessing affirmed the reliability, and convergent validity of the adapted survey was confirmed through comparison to Influencing Factors of Nursing Students' Clinical Judgment (IFNSCJ). The adaptation process of the SSW-NCP resulted in a conceptually equivalent translated version, which is comparable to the original version and is acceptably valid and reliable. Knowing the proficiency of nursing students as future nurses in writing nursing care plans can provide accurate professional information for better educational and practical level programming and management that can enhance nursing practice. The target group of survey was nursing students who contributed and participated in the current study.

Torsion Geometry 5-Fold Symmetry, Anholonomic Phases, Klein Bottle Logophysics, Chaos, Resonance: Applications Towards a Novel Paradigm for the Neurosciences and Consciousness

Torsion Geometry 5-Fold Symmetry, Anholonomic Phases, Klein Bottle Logophysics, Chaos, Resonance: Applications Towards a Novel Paradigm for the Neurosciences and Consciousness

Exit or stay: A critical incident analysis of decision-making in conflict-torn countries

Deploying small world representation logic, we examine the context-specific factors that inform managerial decision-making in conflict-torn countries. Drawing on insights from thirty-one managers, we spotlight nine higher-order heuristics that commonly inform MNEs’ mental representations and their managers’ decision to exit or stay. These heuristics were identified by categorising the commonalities arising from our respondents’ accounts on what information they search for (discovery heuristics) and how it was evaluated (evaluation heuristics). We discovered that information accessibility, conditioned by firms’ in-country experiences, is paramount. Furthermore, since employees are strategy shapers, they can undermine the resilience-enhancing benefits of operational flexibility in conflict-torn countries.

Logical Blocks for Fault-Tolerant Topological Quantum Computation

Logical gates constitute the building blocks of fault-tolerant quantum computation. While quantum error-corrected memories have been extensively studied in the literature, explicit constructions and detailed analyses of thresholds and resource overheads of universal logical gate sets have so far been limited. In this paper, we present a comprehensive framework for universal fault-tolerant logic motivated by the combined need for platform-independent logical gate definitions, flexible and scalable tools for numerical analysis, and exploration of novel schemes for universal logic that improve resource overheads. Central to our framework is the description of logical gates holistically in a way which treats space and time on a similar footing. Focusing on schemes based on surface codes, we introduce explicit, but platform-independent representations of topological logic gates -- called logical blocks -- and generate new, overhead-efficient methods for universal quantum computation. As a specific example, we propose fault-tolerant schemes based on surface codes concatenated with more general low-density parity check (LDPC) codes. The logical blocks framework enables a convenient mapping from an abstract description of the logical gate to a precise set of physical instructions for both circuit-based and fusion-based quantum computation (FBQC). Using this, we numerically simulate a surface-code-based universal gate set implemented with FBQC, and verify that their thresholds are consistent with the bulk memory threshold. We find that boundaries, defects, and twists can significantly impact the logical error rate scaling, with periodic boundary conditions potentially halving the resource requirements. Motivated by the favorable logical error rates for boundaryless computation, we introduce a novel computational scheme based on the teleportation of twists that may offer further resource reductions.

A Theory of Structured Propositions

This paper argues that the theory of structured propositions is not undermined by the Russell-Myhill paradox. I develop a theory of structured propositions in which the Russell-Myhill paradox doesn’t arise: the theory does not involve ramification or compromises to the underlying logic, but rather rejects common assumptions, encoded in the notation of the λ-calculus, about what properties and relations can be built. I argue that the structuralist had independent reasons to reject these underlying assumptions. The theory is given both a diagrammatic representation and a logical representation in a novel language. In the latter half of the paper I turn to some technical questions concerning the treatment of quantification and demonstrate various equivalences between the diagrammatic and logical representations and a fragment of the λ-calculus.

PROPOSITIONAL ANALYSIS AS A WAY OF REVEALING UNDERLYING CULTURAL MEANINGS IN THE TEXT OF OMENS

Background. The importance of the study is due to the attention to the picture of the world, the logic of mythopoetic thinking and mythopoetic representations of nature inherent in the Russian folk consciousness.
 Purpose. The article analyses the types and structure of event propositions of Russian ornithological omens with subjective dominance.
 Materials and methods. The material is about 350 Russian ornithological omens with a subjective dominant. The sources of the study are dictionaries of the Russian language and collections of omens, beliefs, superstitions, as well as works on Russian omens. The main method of research is the analysis of propositions. In addition, such methods as the method of classification and ethno-cultural analysis were used in the work.
 Results. The analysis of the types and structure of the event proposition in Russian ornithological omens with the subject dominant revealed the actual elements of the propositional semantics of this type of omens: these are the propositions “(over)movement” and “action”. Several semantic layers of the text of omens have been studied: proper propositional, intra-propositional and prepositional. It shows the advantage of propositional analysis in comparison with the cognitive (frame) and structural-semantic analysis of Russian folk omens, widespread in modern linguistics, which is that the propositional analysis of omens allows to identify models that reflect ways of cognition and evaluation of reality.
 Practical implications. The results of the analysis can be used to describe small folklore genres, as well as in pedagogical activities, in particular in the teaching of folklore.

An Alternative Definition of Stable Models Via Łukasiewicz Logic

Extensions of G3 (3-valued Godel logic) were studied as tools for knowledge representation and nonmonotonic reasoning. One of these extensions was studied and baptized as G′ 3 by Osorio et al. as a tool to define semantics of logic programming. In this work, we will explore the possibility to use another fuzzy logic for knowledge representation. In particular, we show that Łukasiewicz 3-valued logic (for short, Ł3) can be used for knowledge representation based on logic programming. Firstly, we prove that the definition of stable model for Ł3 is equivalent to the obtained through G3 for augmented programs, but when we consider more general programs we obtain more answers for stable models on Ł3 than G3. Finally, we present and explore a new definition of stable model based on Lukasiewicz n-valued logic via the use of Monteiro-Baaz ∆ operator.

Design considerations for a hierarchical semantic compositional framework for medical natural language understanding.

Medical natural language processing (NLP) systems are a key enabling technology for transforming Big Data from clinical report repositories to information used to support disease models and validate intervention methods. However, current medical NLP systems fall considerably short when faced with the task of logically interpreting clinical text. In this paper, we describe a framework inspired by mechanisms of human cognition in an attempt to jump the NLP performance curve. The design centers on a hierarchical semantic compositional model (HSCM), which provides an internal substrate for guiding the interpretation process. The paper describes insights from four key cognitive aspects: semantic memory, semantic composition, semantic activation, and hierarchical predictive coding. We discuss the design of a generative semantic model and an associated semantic parser used to transform a free-text sentence into a logical representation of its meaning. The paper discusses supportive and antagonistic arguments for the key features of the architecture as a long-term foundational framework.

A Solicitous Approach to Smart Contract Verification

Smart contracts are tempting targets of attacks, as they often hold and manipulate significant financial assets, are immutable after deployment, and have publicly available source code, with assets estimated in the order of millions of dollars being lost in the past due to vulnerabilities. Formal verification is thus a necessity, but smart contracts challenge the existing highly efficient techniques routinely applied in the symbolic verification of software, due to specificities not present in general programming languages. A common feature of existing works in this area is the attempt to reuse off-the-shelf verification tools designed for general programming languages. This reuse can lead to inefficiency and potentially unsound results, as domain translation is required. In this article, we describe a carefully crafted approach that directly models the central aspects of smart contracts natively, going from the contract to its logical representation without intermediary steps. We use the expressive and highly automatable logic of constrained Horn clauses for modeling and instantiate our approach to the Solidity language. A tool implementing our approach, called Solicitous , was developed and integrated into the SMTChecker module of the Solidity compiler solc. We evaluated our approach on an extensive benchmark set containing 22,446 real-world smart contracts deployed on the Ethereum blockchain over a 27-month period. The results show that our approach is able to establish safety of significantly more contracts than comparable, publicly available verification tools, with an order of magnitude increase in the percentage of formally verified contracts.

LHP: Logical hypergraph link prediction

Logical knowledge mining has become increasingly important as it is the foundation of precise reasoning, such as for clinical diagnosis or chemical reaction discovery. Knowledge hypergraphs provide a natural format for expressing inherently high-order relationships beyond pairwise associations. Although logical knowledge (the conjunct operator in first-order logic) is apparently a higher-order relation that can be represented by a hypergraph, methods of representing logical knowledge in this form and completing knowledge by hyperlink prediction have not yet been explored. In this study, logical knowledge is represented by directed hyperedges and effectively quantified by geometric operations in a neural network. The proposed logical hyperlink predictor (LHP) leverages logical knowledge features including permutation invariant and information aggregation of the logical ‘conjunct’ operation. LHP captures logical representation as a whole unit containing the different relationship types embedded within separate hyperedges, making it the novel method to integrate logical knowledge contained within hyperedges. We conduct extensive experiments on the iAF1260b, iJO1366, USPTO, and our Chinese Medical High-order Relational (CMHR) dataset. LHP achieved best performance with linear complexity compared to the state-of-the-art hyperlink prediction methods on a mean area under the receiver operating characteristic curve (AUC), Macro_F1 and accuracy. It was particularly effective on the CMHR demonstrating the importance of logical knowledge representation in the medical field. LHP also achieved a mean AUC of 0.924 in performing hyperedge relationship classification on the CMHR.

Detached retinas: empathy and the transmedial interstices of RAI fiction

ABSTRACT In this essay, we analyse two mainstream Italian TV dramas about the Mediterranean crossing produced by the Italian national public broadcasting company RAI. Lampedusa dall’orizzonte in poi (2016, Marco Pontecorvo) and I fantasmi di Portopalo (2017a,b Alessandro Angelini) were both two-part mini-series broadcast in prime-time slots on consecutive nights on RAI 1. Inspired by real events which took place in 2008 and 1996, respectively, the first features the well-known actor Claudio Amendola, while the second stars Giuseppe Fiorello, perhaps the most popular face on Italian state television. The essay examines the ways in which these two specifically national productions both reproduce conventional media representations of migration and offer the viewer new ways to approach the topic through their transmedial presence on multiple platforms. We analyse the narratives and cinematography of the films themselves and explore how the star personae of the main actors and their appearances across different platforms affect audience reception. Our argument is indebted on work done in the field of critical race theory to illuminate the representational logics of agency in the Mediterranean and the definitions of the human which they produce.

Utilizing XMG-Based Synthesis to Preserve Self-Duality for RFET-Based Circuits

Individual transistors based on emerging reconfigurable nanotechnologies exhibit electrical conduction for both types of charge carriers. These transistors [referred to as reconfigurable field-effect transistors (RFETs)] enable dynamic reconfiguration to demonstrate either a p- or an n-type functionality. This duality of functionality at the transistor level is efficiently abstracted as a self-dual Boolean logic, that can be physically realized with fewer RFET transistors compared to the contemporary CMOS technology. Consequently, to achieve better area reduction for RFET-based circuits, the self-duality of a given circuit should be preserved during logic optimization and technology mapping. In this article, we specifically aim to preserve self-duality by using Xor-majority graphs (XMGs) as the logic representation during logic synthesis and technology mapping. We propose a synthesis flow that uses new restructuring techniques, called rewriting and resubstitution for XMGs to preserve self-duality during technology-independent logic synthesis. For technology mapping, we use a novel open-source and a logic-representation agnostic mapping tool. Using the above-proposed XMG-based flow, we demonstrate its benefits by comparing post-mapping areas for synthetic and cryptographic benchmarks with three different synthesis flows: 1) AIG-based optimization and AIG-based mapping; 2) XMG-based optimization with AIG-based mapping; and 3) AIG-based optimization with logic-representation agnostic mapping. Our experiments show that the proposed XMG-based flow efficiently preserves self-duality and achieves the best area results for RFET-based circuits (up to 12.36% area reduction) with respect to the baseline.

From Combinatory Categorial Grammar to the Calculus of Constructions: A Review of ccg2lambda.

The following is an overview of the concepts and systems necessary to build an understanding of the framework from ccg2lambda: A Compositional Semantics System, which produces logical semantic representations of natural language sentences. These representations are used in tandem with a theorem prover to conduct inferences. But, to the reader unfamiliar with the various tools within computer science, linguistics, and mathematics that were used to construct ccg2lambda and its dependencies, it can be difficult to understand the inner workings of the framework. Thus, an explication of these concepts could be useful for fostering further development. Concepts such as mathematical logic, combinatory categorial grammar, the calculus of constructions, and interactive theorem provers are covered, as well as the two systems C&C and ccg2lambda. A functional version of the ccg2lambda framework can be found at https://github.com/ajung202/ccg2lambda.

Seeing inferences: brain dynamics and oculomotor signatures of non-verbal deduction

We often express our thoughts through words, but thinking goes well beyond language. Here we focus on an elementary but basic thinking process, disjunction elimination, elicited by elementary visual scenes deprived of linguistic content, describing its neural and oculomotor correlates. We track two main components of a nonverbal deductive process: the construction of a logical representation (A or B), and its simplification by deduction (not A, therefore B). We identify the network active in the two phases and show that in the latter, but not in the former, it overlaps with areas known to respond to verbal logical reasoning. Oculomotor markers consistently differentiate logical processing induced by the construction of a representation, its simplification by deductive inference, and its maintenance when inferences cannot be drawn. Our results reveal how integrative logical processes incorporate novel experience in the flow of thoughts induced by visual scenes.

A Sequence Labeling Method for First-order Logic Representation

Extracting logic knowledge is an important part of natural language understanding. This study introduces a new dataset for the purpose of measuring the model's ability to transfer natural language to logic form. Since logic represents how various concepts infer and reason from/to each other, it is essential to learn logical structure in any form of language while trying to comprehend its meaning of it. There have recently been many interests in deploying machine learning and deep learning methods for extracting logical knowledge and representing logic from natural language. The promising generative model that applied to recent sequence labeling work is used in the task of representing logic. Experiments have shown that generative methods can extract logic form from natural language texts. To be more specific, a sequence-to-sequence model is quite a convenient option when it deals with extraction tasks. The model provided in this study would be inspiring for future studies to work out more efficient solutions.

A Morphological Analysis of Martin Luther King Jr’s “I HAVE A DREAM” Speech: a Compositional Semantic Perspective

This research work has investigated the importance of linguistic morphology in the construction of new lexemes and grammatically conditioned words on the first hand and the way both derivational and inflectional morphemes function to carry and impart compositional meaning in text on the other. Premised on the objective of raising more awareness on the significance of morphological research, this paper has applied both the quantitative and qualitative analysis methods to the historic speech “I Have a Dream” by the African American civil rights figurehead Martin Luther King Jr. The scientific roadmap thus carved has led its process through the identification, labelling and numbering of the distinctive derivational (50 /40%) and inflectional (75 / 60%) morphemes. A furthering of the quantitative input has displayed an outstanding use of nominalisations with nouns derived from adjectives 17 [13.6%] and from verbs 12 [9.6%] with bound morphemes such as “ity”, “ice”, “ation”, “tion”, “or”, and “dom”. On the inflectional part, the prevailing use of regular and irregular plural number imparting morphemes (47 / 37.6%) together with tense inflections (16 / 12.8%) pair up to confirm, in a qualitative analytical approach, the ideological perspective of the speaker to include the largest anonymous members of the African American community as the intended beneficiaries of his unquenchable soft but vibrant battle for freedom. The use of tense indicating morphemes has revealed the presence of a threefold tense progression from the past tense (simple past and past perfect) to the simple present and then to the future. The crosscheck of the semantics of such morphemic operations has uncovered the perspective of Martin Luther King Jr for the logical representation of the sufferings of the Black community and liberation struggles in the past, the need to keep the battle going in the present time with the conviction of brighter days in the future.

Knowledge representation and reasoning using interconnected uncertain rules for describing workflows in complex systems

Knowledge representation and reasoning (KRR) in complex systems (CSs) usually require facts from multiple experts having complementary backgrounds to fuse together. Consequently, such KRR methods should provide universal modeling languages close to human reasoning, with increased expressiveness and efficient capabilities to describe uncertainties. In this context, this paper introduces a new modeling formalism entitled Hybrid Logic-Algebraic Relational Modeling which is based on combining logic, probabilities, numerical information and network representations. The behavior, facts and workflows in a CS can be described using an environment of interconnected models enclosing sets of logical rules with attached probabilistic trust factors and links regarding logical attributes and numerical parameters. The logical and probabilistic inference applied to the modeling environment gives valuable knowledge to designers and decision-makers so that they can develop procedures or take actions in managing the CS. In this article, the proposed approach is completely formalized, from concept to definition and proofs and up to implementation, while its usage is illustrated within a complex economic, logistical, economical and technical scenario.

Uncovering illicit supply networks and their interfaces to licit counterparts through graph-theoretic algorithms

The rapid market growth of different illicit trades in recent years can be attributed to their discreet, yet effective, supply chains. This article presents a graph-theoretic approach for investigating the composition of illicit supply networks using limited information. Two key steps constitute our strategy. The first is the construction of a broad network that comprises entities suspected of participating in the illicit supply chain. Two intriguing concepts are involved here: unification of alternate Bills-of-materials and identification of entities positioned at the interface of licit and illicit supply chain; logical graph representation and graph matching techniques are applied to achieve those objectives. In the second step, we search for a set of dissimilar supply chain structures that criminals might likely adopt. We provide an integer linear programming formulation as well as a graph-theoretic representation for this problem, the latter of which leads us to a new variant of Steiner Tree problem: Generalized Group Steiner Tree Problem. Additionally, a three-step algorithmic approach of extracting single (cheapest), multiple and dissimilar trees is proposed to solve the problem. We conclude this work with a semi-real case study on counterfeit footwear to illustrate the utility of our approach in uncovering illicit trades. We also present extensive numerical studies to demonstrate scalability of our algorithms.