11,519 research outputs found
With a Few Square Roots, Quantum Computing Is as Easy as Pi
Rig groupoids provide a semantic model of Π, a universal classical reversible programming language over finite types. We prove that extending rig groupoids with just two maps and three equations about them results in a model of quantum computing that is computationally universal and equationally sound and complete for a variety of gate sets. The first map corresponds to an 8th root of the identity morphism on the unit 1. The second map corresponds to a square root of the symmetry on 1+1. As square roots are generally not unique and can sometimes even be trivial, the maps are constrained to satisfy a nondegeneracy axiom, which we relate to the Euler decomposition of the Hadamard gate. The semantic construction is turned into an extension of Π, called √Π, that is a computationally universal quantum programming language equipped with an equational theory that is sound and complete with respect to the Clifford gate set, the standard gate set of Clifford+T restricted to ≤2 qubits, and the computationally universal Gaussian Clifford+T gate set
Good enough processing: what have we learned in the 20 years since Ferreira et al. (2002)?
Traditionally, language processing has been thought of in terms of complete processing of the input. In contrast to this, Ferreira and colleagues put forth the idea of good enough processing. The proposal was that during everyday processing, ambiguities remain unresolved, we rely on heuristics instead of full analyses, and we carry out deep processing only if we need to for the task at hand. This idea has gathered substantial traction since its conception. In the current work, I review the papers that have tested the three key claims of good enough processing: ambiguities remain unresolved and underspecified, we use heuristics to parse sentences, and deep processing is only carried out if required by the task. I find mixed evidence for these claims and conclude with an appeal to further refinement of the claims and predictions of the theory
Cyclic proof systems for modal fixpoint logics
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
A Preliminary Semantic Corpus-Based Study on the Classifier 架 ( jià ) and Its Implications for Teaching Chinese Classifiers
In this pilot study, diachronic semantic analysis is employed to probe the origin and semantic evolution of the classifier 架 ( jià ). The study aims to achieve three objectives. Firstly, it intends to probe the emergence and development of the Chinese classifier 架 ( jià ). Secondly, it seeks to attest to the perspective of the fundamental role of human cognition and perception in the classifier language system, as indicated by Tai and Wang (1990). Finally, it suggests pragmatic classifiers teaching approaches in alignment with cognitive linguistic perceptions. The preliminary analysis of this study signifies that the classifier 架 ( jià ) is not an arbitrary linguistic device. Instead, its utilization throughout history reflects human categorization in reliance on the perceptual property of the supporting framework of the referents. To improve the efficiency of teaching Chinese classifiers and provide learners with a more natural and comprehensive acquisition mode, future studies on classifier acquisition are expected to align with the conceptual structure of the classifiers' domains and the cognitive linguistic approach
An examination of the verbal behaviour of intergroup discrimination
This thesis examined relationships between psychological flexibility, psychological inflexibility, prejudicial attitudes, and dehumanization across three cross-sectional studies with an additional proposed experimental study. Psychological flexibility refers to mindful attention to the present moment, willing acceptance of private experiences, and engaging in behaviours congruent with one’s freely chosen values. Inflexibility, on the other hand, indicates a tendency to suppress unwanted thoughts and emotions, entanglement with one’s thoughts, and rigid behavioural patterns. Study 1 found limited correlations between inflexibility and sexism, racism, homonegativity, and dehumanization. Study 2 demonstrated more consistent positive associations between inflexibility and prejudice. And Study 3 controlled for right-wing authoritarianism and social dominance orientation, finding inflexibility predicted hostile sexism and racism beyond these factors. While showing some relationships, particularly with sexism and racism, psychological inflexibility did not consistently correlate with varied prejudices across studies.
The proposed randomized controlled trial aims to evaluate an Acceptance and Commitment Therapy intervention to reduce sexism through enhanced psychological flexibility. Overall, findings provide mixed support for the utility of flexibility-based skills in addressing complex societal prejudices. Research should continue examining flexibility integrated with socio-cultural approaches to promote equity
On Wondering: The Epistemology of A Questioning Attitude
An emerging trend in contemporary epistemology departs from the traditional preoccupation with the nature of knowledge, belief, evidence, justification, and the problems of skepticism. This trend focuses instead on the nature of inquiry itself and especially on the role of questions and questioning attitudes that arise in and define that activity. Naturally, this emerging trend calls for a philosophical exploration of the nature of questioning attitudes like curiosity and wondering, and of the various epistemological considerations pertaining to them. Consequently, this project primarily addresses two questions: what does it mean to wonder? And what is required to wonder well?
The project is thus both descriptive and normative, aiming to pin down the place that wondering has in our ontology of epistemologically significant mental states and to determine what kinds of prescriptive norms it is subject to in the course of rational inquiry
Fragments and frame classes:Towards a uniform proof theory for modal fixed point logics
This thesis studies the proof theory of modal fixed point logics. In particular, we construct proof systems for various fragments of the modal mu-calculus, interpreted over various classes of frames. With an emphasis on uniform constructions and general results, we aim to bring the relatively underdeveloped proof theory of modal fixed point logics closer to the well-established proof theory of basic modal logic. We employ two main approaches. First, we seek to generalise existing methods for basic modal logic to accommodate fragments of the modal mu-calculus. We use this approach for obtaining Hilbert-style proof systems. Secondly, we adapt existing proof systems for the modal mu-calculus to various classes of frames. This approach yields proof systems which are non-well-founded, or cyclic.The thesis starts with an introduction and some mathematical preliminaries. In Chapter 3 we give hypersequent calculi for modal logic with the master modality, building on work by Ori Lahav. This is followed by an Intermezzo, where we present an abstract framework for cyclic proofs, in which we give sufficient conditions for establishing the bounded proof property. In Chapter 4 we generalise existing work on Hilbert-style proof systems for PDL to the level of the continuous modal mu-calculus. Chapter 5 contains a novel cyclic proof system for the alternation-free two-way modal mu-calculus. Finally, in Chapter 6, we present a cyclic proof system for Guarded Kleene Algebra with Tests and take a first step towards using it to establish the completeness of an algebraic counterpart
The role of intonation and context in lack of necessity meanings in negated deontic necessity modals in child Romanian
The current paper experimentally addresses the question of whether Romanian 5-year-olds interpret negated deontic necessity modals as interdiction initially, and to what extent intonation and situational context may act as cues for a more adult-like interpretation. We find that, in the absence of situational context, children initially interpret all negated deontic modals as interdiction. Prosodic cues are on their own not enough to lead to an adult interpretation. However, in the presence of situational context, children are able to tease lack of necessity and interdiction apart and even show sensitivity to prosodic differences among negated modals
A clinical decision support system for detecting and mitigating potentially inappropriate medications
Background: Medication errors are a leading cause of preventable harm to patients. In older adults, the impact of ageing on the therapeutic effectiveness and safety of drugs is a significant concern, especially for those over 65. Consequently, certain medications called Potentially Inappropriate Medications (PIMs) can be dangerous in the elderly and should be avoided. Tackling PIMs by health professionals and patients can be time-consuming and error-prone, as the criteria underlying the definition of PIMs are complex and subject to frequent updates. Moreover, the criteria are not available in a representation that health systems can interpret and reason with directly.
Objectives: This thesis aims to demonstrate the feasibility of using an ontology/rule-based approach in a clinical knowledge base to identify potentially inappropriate medication(PIM). In addition, how constraint solvers can be used effectively to suggest alternative medications and administration schedules to solve or minimise PIM undesirable side effects.
Methodology: To address these objectives, we propose a novel integrated approach using formal rules to represent the PIMs criteria and inference engines to perform the reasoning presented in the context of a Clinical Decision Support System (CDSS). The approach aims to detect, solve, or minimise undesirable side-effects of PIMs through an ontology (knowledge base) and inference engines incorporating multiple reasoning approaches.
Contributions: The main contribution lies in the framework to formalise PIMs, including the steps required to define guideline requisites to create inference rules to detect and propose alternative drugs to inappropriate medications. No formalisation of the selected guideline (Beers Criteria) can be found in the literature, and hence, this thesis provides a novel ontology for it. Moreover, our process of minimising undesirable side effects offers a novel approach that enhances and optimises the drug rescheduling process, providing a more accurate way to minimise the effect of drug interactions in clinical practice
Explainable text-based features in predictive models of crowdfunding campaigns
Reward-Based Crowdfunding offers an opportunity for innovative ventures that would not be supported through traditional financing. A key problem for those seeking funding is understanding which features of a crowdfunding campaign will sway the decisions of a sufficient number of funders. Predictive models of fund-raising campaigns used in combination with Explainable AI methods promise to provide such insights. However, previous work on Explainable AI has largely focused on quantitative structured data. In this study, our aim is to construct explainable models of human decisions based on analysis of natural language text, thus contributing to a fast-growing body of research on the use of Explainable AI for text analytics. We propose a novel method to construct predictions based on text via semantic clustering of sentences, which, compared with traditional methods using individual words and phrases, allows complex meaning contained in the text to be operationalised. Using experimental evaluation, we compare our proposed method to keyword extraction and topic modelling, which have traditionally been used in similar applications. Our results demonstrate that the sentence clustering method produces features with significant predictive power, compared to keyword-based methods and topic models, but which are much easier to interpret for human raters. We furthermore conduct a SHAP analysis of the models incorporating sentence clusters, demonstrating concrete insights into the types of natural language content that influence the outcome of crowdfunding campaigns
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