Default Logic Research Articles

Factors Associated With Default of Treatment and Follow-Up Among Patients With Cancer: A Cross-Sectional Study From a Lower-Middle-Income Country.

Desirable outcomes during the treatment of patients with cancer require adherence to evaluation, treatment, and follow-up. This study aimed to evaluate the factors associated with default in patients with cancer. We included patients with a histologically confirmed diagnosis of cancer who defaulted during evaluation, treatment, and follow-up. All patients' detailed demographic and clinical data were recorded. Those lost to follow-up were interviewed telephonically. The factors associated with default were noted. Descriptive statistics were used to compute the demographic and clinical characteristics. In total, 172 patients were included. Geriatric and female patients were 38.9% and 37.2%, respectively. Fifty-eight percent of the patients lived in rural areas, whereas 45.9% were illiterate. More than one third (34.3%) of the patients who defaulted received the curative-intent treatment, whereas 62.1% of patients had a good performance status immediately before default. The average distance traveled by the patients to reach the cancer facility was 143 ± 13.15 km. The most common reasons for default were the lack of social support, financial constraints, difficulty in commuting, and too sick to come in 45 (26.2%), 35 (20.3%), 28 (16.3%), and 23 (13.4%) patients, respectively. Twenty-nine (16.9%) patients reported more than one reason for default. Lack of social support, financial constraints, transportation barriers, and inadequate counseling by the health care provider serve as barriers to uninterrupted cancer care. These factors are often interrelated and can be attenuated by adopting the hub and spoke model. Simultaneously, a good relationship between the patient and the health care provider fostered by appropriate counseling is imperative to increase adherence to cancer treatment and improve the outcome.

Are generics quantificational?

The standard view about generic generalizations is that they have a tripartite quantificational logical form involving a phonologically null quantificational expression called ‘Gen’. However, proponents of the cognitive defaults theory of generics have forcefully rejected this view, instead arguing that generics express the default generalizations of our cognitive system, and, as such, they are different in kind from quantificational generalizations. While extant criticism of the cognitive defaults theory has focused on the extent to which it is supported by the empirical evidence, there has been little discussion of a neglected, albeit essential, theoretical argument in its defence, namely, that generics cannot be quantificational because they lack a central logical property of quantifiers: isomorphism invariance. This paper addresses this lacuna by considering and rejecting this argument. Consequently, an essential argument in favour of the cognitive default theory is found wanting.

Strong Backdoors for Default Logic

In this article, we introduce a notion of backdoors to Reiter’s propositional default logic and study structural properties of it. Also we consider the problems of backdoor detection (parameterised by the solution size) as well as backdoor evaluation (parameterised by the size of the given backdoor) for various kinds of target classes (CNF, KROM, MONOTONE) and all SCHAEFER classes. Also, we study generalisations of HORN-formulas, namely QHORN, RHORN, as well as DUALHORN. For these classes, we also classify the computational complexity of the implication problem. We show that backdoor detection is fixed-parameter tractable for the considered target classes and prove a complete trichotomy for backdoor evaluation. The problems are either fixed-parameter tractable, para-DeltaP2-complete, or para-NP-complete, depending on the target class.

Modeling Deep Disagreement in Default Logic

Default logic has been a very active research topic in artificial intelligence since the early 1980s, but has not received as much attention in the philosophical literature thus far. This paper shows one way in which the technical tools of artificial intelligence can be applied in contemporary epistemology by modeling a paradigmatic case of deep disagreement using default logic. In §1 model-building viewed as a kind of philosophical progress is briefly motivated, while §2 introduces the case of deep disagreement we aim to model. On the heels of this, §3 defines our formal framework, viz., a refined Horty-style default logic. §4 then uses the framework to model deep disagreement, and finally §5 provides a critical discussion of the result.

Who gets duped? The impact of education on fraud detection in an investment task

Many financial scandals appear to depend on a lack of skepticism on the part of their victims. Sophisticated investors trusted Bernie Madoff, for example, despite early warning signs of implausible returns. Our study investigates how education explains fraud detection in financial decision-making. In a simple survey, economics and finance students are asked to make an investment recommendation from among four hypothetical funds, including one based on Madoff’s fund. We use Truth Default Theory to explain our results. We show that education increases the likelihood that students are suspicious of Madoff’s fund, and that for students whose suspicions are aroused, education makes them less likely to choose the Madoff fund.

Non-deterministic approximation fixpoint theory and its application in disjunctive logic programming

Approximation fixpoint theory (AFT) is an abstract and general algebraic framework for studying the semantics of nonmonotonic logics. It provides a unifying study of the semantics of different formalisms for nonmonotonic reasoning, such as logic programming, default logic and autoepistemic logic. In this paper, we extend AFT to dealing with non-deterministic constructs that allow to handle indefinite information, represented e.g. by disjunctive formulas. This is done by generalizing the main constructions and corresponding results of AFT to non-deterministic operators, whose ranges are sets of elements rather than single elements. The applicability and usefulness of this generalization is illustrated in the context of disjunctive logic programming.

Effect of shipping company demographic characteristics on cabotage vessel finance and repayment in Nigeria

The research examined the effect of shipping company demographic characteristics on cabotage vessel finance and repayment in Nigeria. The Nigerian Maritime Administration and Safety Agency (NIMASA) have been concerned about the inability of the Ship Acquisition and Ship Building Fund (SASBF) beneficiaries to pay back disbursed loans fully, resulting in the suspension of further disbursement of the fund required for the development of Nigerian local content capacity. The Cabotage Act 2003 was intended for local content development of shipping and maritime logistics capacity. The fund realized through a 2% surcharge on cabotage trade has accrued since inception, but no shipowner has benefited from the CVFF loan. The study relied on both primary and secondary data. Data was collected through a well-structured questionnaire. The study utilized a Statistical Product Service Solution (SPSS v. 23) and a one-sample chi-square test as statistical tools for data analysis. The results reveal that demographic characteristics of shipping companies, such as age, number of vessels, number of employees and total annual revenue, significantly influence CVFF loan repayment. Purpose: To identify and analyze the shipping company demographic characteristics which influence cabotage vessel finance and repayment in Nigeria. The findings suggested practical steps for effective CVFF loan disbursement and reliable loan recovery. Methodology: The study utilized Statistical Product Service Solution (SPSS v. 23) and a one-sample chi-square test as statistical tools for data analysis. Results: The demographic characteristics of a shipping company, such as company age in years, number of employees, share capital, number of vessels and shipyards as well as the age of vessels and shipyards has a significant influence on her Character, Capacity, Credibility, Capital, Conditions, Collateral and Creditworthiness of the organization. Theoretical contribution: The research contributed to exploring, understanding, and applying the probability of credit default theory in shipping finance loan repayment. The demographic internal microeconomic organization Character, Capacity, Credibility, Capital, Conditions, Collateral and Creditworthiness significantly affects the ability of CVFF fund beneficiaries to repay the loans. Practical implications: Prospective borrower indigenous maritime operators should be duly and professionally evaluated to ensure sustainable cash flow and revenue projection during and after granting CVFF loans to guarantee complete repayment.

Assumption-based argumentation for extended disjunctive logic programming and its relation to nonmonotonic reasoning

The motivation of this study is that Reiter’s default theory as well as assumption-based argumentation frameworks corresponding to default theories have difficulties in handling disjunctive information, while a disjunctive default theory (ddt) avoids them. This paper presents the semantic correspondence between generalized assumption-based argumentation (ABA) and extended disjunctive logic programming as well as the correspondence between ABA and nonmonotonic reasoning approaches such as disjunctive default logic and prioritized circumscription. To overcome the above-mentioned difficulties of ABA frameworks corresponding to default theories, we propose an assumption-based framework (ABF) translated from an extended disjunctive logic program (EDLP) since an EDLP can be translated into a ddt. Our ABF incorporates explicit negation and the connective of disjunction “|” to Heyninck and Arieli’s ABF induced by a disjunctive logic program. In this paper, first, we show how arguments are constructed from disjunctive rules in our proposed ABF. Then, we show the correspondence between answer sets of an EDLP P and stable extensions of the ABF translated from P with trivialization rules. After defining rationality postulates, we show answer sets of a consistent EDLP are captured by consistent stable extensions of the translated ABF with no trivialization rules. Finally, we show the correspondence between ABA and disjunctive default logic (resp. prioritized circumscription). The relation between ABA and possible model semantics of EDLPs is also discussed.

CE Workshop 09: Cast Aside Traditional Notions of Statistical Significance, and Focus Instead on Characterizing the Magnitude of Effects that are Clinically or Scientifically Relevant

Abstract & Learning ObjectivesThere is an ongoing debate among statisticians and discipline scientists about the consequences of our persistent, dogmatic reliance on evaluating all statistical results as meaningful if and only if "p<0.05," regardless of context. This was never the intended goal of Ronald Fisher, nevertheless scientists have adopted it as a convenience, and the decades long dependence on "p<0.05" has had important negative consequences. In this presentation, I review common misconceptions about interpreting p-values, why we should consider de-emphasizing p-values, and why scientists should rely more on practical, clinical, or scientifically meaningful differences over arbitrary cut-offs. I will present several different metrics for evaluating and reporting effect magnitude, and whether or not data support the null vs. alternative hypothesis, under the frequentist paradigm, how Bayesian methods can augment or replace frequentist analyses, and a few options that help to clarify how important a finding may be. Throughout this talk, I advocate that discipline scientists take charge of sharing scientific results that are not based merely on arbitrary p-value cutoffs and other default logic, but instead based on their content expertise, in light of all of the specific relevant aspects of experimental design and experimental data, balancing the consequences of Type I vs Type II errors appropriately, and focusing on characterizing effects, rather than dichotomizing research into only two categories of importance (significant vs. not).Upon conclusion of this course, learners will be able to: 1.Discuss what p-values mean and how they are commonly misinterpreted.2.Explain the leading arguments promoted by the American Statistical Association with regard to why science should carefully reconsider if and how p-values should continue to dominate our decisions about what research should be published, and how scientists should be evaluating its worth.3.Apply new practices in how to evaluate and publish their own research, as well as how to evaluate research appearing in peer-reviewed journals, whether as consumers, reviewers, or editors.

Loss to follow-up in a newborn hearing screening program in Saudi Arabia.

Newborn hearing screening (NHS) program was officially initiated in Saudi Arabia in 2016. Although the rate of follow-up default is considered one of the major challenges to the NHS program, no studies have investigated the NHS rate of follow-up default and its reasons in Saudi Arabia. This study aimed to investigate the rate of follow-up default in a hospital-based NHS program and the possible reasons for it. All newborns who were delivered at a tertiary hospital-based NHS program between June 2020 and February 2022 were retrospectively included. The number of live births, newborns who passed NHS, newborns who referred NHS, and newborns who did not complete the appropriate screening or diagnostic stages were reviewed. In a prospective study, parents of all newborns who defaulted the follow-up on screening or diagnosis were telephonically interviewed about the reasons for their follow-up default. In total, 2312 newborns were screened. Screening coverage of 96% and referral rate of 0.6% were found, which align well with the international benchmark. The follow-up default was 18%, which was higher than the benchmark. Parents of all newborns who defaulted the follow-up (n=424) were also included. The most frequent reasons for follow-up default were related to the parents' unawareness of the recommended follow-up screening (39.5%) and their perception that follow-up was not necessary (24.7%). Coronavirus disease 2019 was also reported by 15.8% of the parents as a reason for follow-up default. Lack of knowledge regarding recommendations made for follow-up and the importance of NHS were the most common reasons for default. Reducing follow-up defaults is essential for successful NHS programs, which can be achieved by implementing a tracking system to remind and encourage parents. Further studies are needed to evaluate the national NHS and investigate the reasons for follow-up defaults from different demographic regions in Saudi Arabia.

Model selection in multivariate adaptive regressions splines (MARS) using alternative information criteria

Multivariate Adaptive Regression Splines (MARS) is a useful non-parametric regression analysis method that can be used for model selection in high-dimensional data. Since MARS can identify and model complex, non-linear relationships between the dependent variable and independent variables without requiring any assumptions, it has advantage over simple linear regression techniques. Also, for simplifying the model building process and preventing overfitting, MARS can select automatically the variables to be included in the model, which is useful for datasets with many variables. While MARS is a flexible non-parametric regression method, generalized cross validation (GCV) technique is used within the MARS framework to avoid overfitting and to select the best model. GCV criterion is widely used and can be effective in many situations, however it has some criticism. These criticism are the arbitrary value of the smoothing parameter used in the algorithm of the GCV criterion and the models obtained using this criterion are high-dimensional. In this paper, it is aimed to obtain the barest model that best explains the relationship between the dependent variable and independent variables by using alternative information criteria (Akaike information criterion (AIC), Schwarz Bayesian criterion (SBC) and information complexity criterion (ICOMP(IFIM)PEU)) instead of the use of smoothing parameters in order to put an end to the criticism. To achieve this goal, a simulation study was first conducted with a data set composed of variables that do and do not contribute to the dependent variable to test the success of the information criteria. As a consequence of this simulation work, when variables (which do not contribute to the dependent variable) are not included in the regression model, it demonstrates the success of the criteria in model selection. As a real data set, the reasons for loan defaults were investigated between the years 2005–2019 by utilizing data from 18 banks operating in Türkiye. The results obtained reveal the success of ICOMP(IFIM)PEU criterion in model selection.

Answer Set Programming (DLV – Clingo):Connect 4 Solver

Answer set programming is an approach that has recently gained a lot of popularity in solving complex problems due to its efficient knowledge representation and reasoning. Knowledge is represented as answer set programs, and reasoning is performed by answer set solvers. Answer set programming enables default reasoning, which is required in commonsense reasoning. In this paper, we discuss the potential role of answer set programming (ASP) in the context of approaches to the development of agents especially in the realm of Computational Logic. So, we focus on the usage of DLV for solving problems in a declarative manner particularly, in the solution of the game “connect four”. Additionally, we present the solution to this same problem from Clingo's perspective. We address this challenge with the ASP system clingo and its grounding and solving components by equipping them with well-defined generic interfaces facilitating the manifold integration efforts.

Connexive Logic, Probabilistic Default Reasoning, and Compound Conditionals

We present two approaches to investigate the validity of connexive principles and related formulas and properties within coherence-based probability logic. Connexive logic emerged from the intuition that conditionals of the form if not-A, thenA, should not hold, since the conditional’s antecedent not-A contradicts its consequent A. Our approaches cover this intuition by observing that the only coherent probability assessment on the conditional event A|A¯\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${A| \\overline{A}}$$\\end{document} is p(A|A¯)=0\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${p(A| \\overline{A})=0}$$\\end{document}. In the first approach we investigate connexive principles within coherence-based probabilistic default reasoning, by interpreting defaults and negated defaults in terms of suitable probabilistic constraints on conditional events. In the second approach we study connexivity within the coherence framework of compound conditionals, by interpreting connexive principles in terms of suitable conditional random quantities. After developing notions of validity in each approach, we analyze the following connexive principles: Aristotle’s theses, Aristotle’s Second Thesis, Abelard’s First Principle, and Boethius’ theses. We also deepen and generalize some principles and investigate further properties related to connexive logic (like non-symmetry). Both approaches satisfy minimal requirements for a connexive logic. Finally, we compare both approaches conceptually.

Nonmonotonic inferences: Classical conclusions in an intuitionistic modal framework

Abstract We introduce a conceptual foundation for nonmonotonic reasoning which integrates an intuitionistic plurimodal logic with classical logic. The need for a multilogical system arises once we understand that to legitimately infer less than certain conclusions, we make two different kinds of assessments: an external one (what are the alternatives) and an internal one (which logic should govern the set of beliefs). We exploit this scheme to capture in novel ways basic nonmonotonic systems such as autoepistemic logic, default logic, one of the best known interpretations of negation-as-failure, as well as some conditional logics of normality. Among the aims of this paper is to explain why there are substantial overlaps between these systems and also to settle some problematic features that are of concern in logical investigations on common sense reasoning.

Target Centred Virtue Ethics

<i>Target Centred Virtue Ethics</i>

Postnatal care services use by mothers: A comparative study of defaulters versus attendees of postnatal clinics in Enugu.

Despite much emphasis on the reproductive health of women, maternal mortality is still high, especially in postnatal period. To assess the prevalence of postnatal care use and reasons for defaults among mothers attending the child immunization clinics in Enugu, Nigeria. This was a cross-sectional comparative study of 400 consecutive nursing mothers who presented at the Institute of Child Health of UNTH and ESUTH, Enugu for Second dose of the Oral Polio Vaccine (OPV2) for their babies at 10 weeks postpartum. Data was collected using Interviewer-administered questionnaire and subsequently analyzed with version 22.0 IBM SPSS software, Chicago, Illinois. A p-value of less than 0.05 was considered as statistically significant. The prevalence of the 6th week postnatal clinic attendance among the mothers was 59%. The majority of the women (60.6%) who had antenatal care by skilled birth attendants attended postnatal clinic. Unawareness and being healthy were the main reasons for not attending postnatal clinic. Following multivariate analysis, place of antenatal (OR = 2.870, 95% C.I = 1.590-5.180, p < 0.001) and mode of delivery (OR = 0.452, 95% C.I = 0.280-0.728, p = 0.001) were the only significant predictors of postnatal clinic attendance (p < 0.05). Postnatal clinic attendance by women in Enugu is still suboptimal. The main reason for non-attendance of the 6th week postnatal clinic was lack of awareness. There is need for healthcare professionals to create awareness about the importance of postnatal care and encourage mothers to attend.

Identification of Financial Distressed Firms at Pakistan Stock Exchange Through Infusion of Corporate Social Responsibility Information into Altman Z-Score

Financial distress is one of the leading reasons for corporate default, foreclosure, and subsequent bankruptcy. Traditionally accounting information-based models have been used to identify the financially distressed firms. Inaccurate identification results in type-I and type- II errors. These errors are attributable to the elements of conservatism and prudence within the accounting information. Enclosure of market information into these models may reduce the quantum of errors and improve the existing ability of these models to accurately identify the financially distressed firms. This study has infused the Corporate Social Responsibility information into the Altman Z-Score. The enclosure has been made using additive index methodology, resulting in formation of a Composite Default Index. 161 non- financial firms listed on the Pakistan Stock Exchange have been taken as the sample over the study period of 2010-2016. The accuracy of Composite default Index has been found significantly better as compared to the Z-Score Default Index as the type-I and type-II errors are reduced by 41% and 132% respectively. This study has implication for the corporate regulators, practitioners, stakeholders and researchers in form of providing a better mechanism to identify the financially distressed firms, future studies may consider other forms of market information and the accounting information-based models to improve upon the same, further.

Assertion and truth default

I argue that a successful assertion may consist exclusively of adding “Speaker has said that p” to the common ground. Other effects of the assertion, such as the assumption by the hearer that the speaker believes p and the addition of p to the common ground, follow from the truth-bias, a cornerstone of Truth Default Theory (Levine 2019). Empirical support for this view comes from what I call minimal assertions, a type of speech act that has the hallmark of an assertion to the extent that it elicits a commitment to the truth of the statement but does not seem to have any of the additional properties usually attached to an assertion, such as an expectation that the speaker believes or knows p. I show that minimal assertions are made in contexts in which the truth bias is inoperative because it is beside the point. I conclude that minimal assertions provide empirical support for the commitment theory of assertion (Geurts 2019).

Modular orders on defaults in formal argumentation

Abstract Default logic and formal argumentation are paradigmatic methods in the study of nonmonotonic inference. Defeasible information often comes in different strengths stemming from different degrees of reliability in epistemic applications or from varying strengths of authorities issuing norms in deontic applications. In both paradigms, methods have been developed to deal with prioritized knowledge bases and normative systems. Questions of comparability of these methods therefore naturally arise. Argumentation theory has been developed with a strong emphasis on unification. It is therefore a desideratum to obtain natural representations of various approaches to (prioritized) default logic within frameworks of structured argumentation, such as ASPIC. Important steps in this direction have been presented in Liao et al. (2016, 2018). In this work, we identify and address some problems in earlier translations, we broaden the focus from total to modular orderings of defaults and we consider non-normal defaults.

Two factor-based models of precedential constraint: a comparison and proposal

The article considers two different interpretations of the reason model of precedent pioneered by John Horty. On a plausible interpretation of the reason model, past cases provide reasons to prioritize reasons favouring the same outcome as a past case over reasons favouring the opposing outcome. Here I consider the merits of this approach to the role of precedent in legal reasoning in comparison with a closely related view favoured by some legal theorists, according to which past cases provide reasons for undercutting (or ‘excluding’) reasons favouring the opposing outcome. After embedding both accounts within a general default logic, I note some important differences between the two approaches that emerge as a result of plausible distinctions between rebutting and undercutting defeat in formal models of legal reasoning. These differences stem from the ‘preference independence’ of undercutting defeat . Undercutting reasons succeed in defeating opposing reasons irrespective of their relative strength. As a result, the two accounts differ in their account of the way in which precedents constrain judicial reasoning. I conclude by suggesting that the two approaches can be integrated within a single model, in which the distinction between undercutting and rebutting defeat is used to account for the distinction between strict and persuasive forms of precedential constraint.