Knowledge Representation and Reasoning

Healthcare data fragmentation and lack of interoperability remain critical challenges in Nigeria, limiting efficient data exchange and evidence-based clinical decision-making. This study proposes a context-aware ontology-based health data model to enhance semantic interoperability across heterogeneous healthcare systems. A Design Science Research (DSR) methodology is adopted to develop a domain-specific ontology that formally captures healthcare concepts, relationships, and constraints using Semantic Web technologies. The model integrates standardized medical terminologies (e.g., SNOMED CT and ICD-10) and introduces a formal data mapping function for consistent semantic interpretation. Additionally, a semantic similarity measure is incorporated to improve concept alignment and support intelligent querying. The proposed ontology is implemented within a simulated Electronic Health Record (EHR) environment and evaluated using interoperability performance metrics. Results demonstrate a significant improvement in interoperability, with the Semantic Interoperability Score increasing from 0.55 to 0.87, representing over 60% enhancement compared to traditional models. Findings confirm that ontology-driven approaches effectively reduce data ambiguity, enhance semantic consistency, and support scalable healthcare system integration. This study contributes a practical and scalable interoperability framework tailored to resource-constrained environments, with direct implications for improving healthcare data management and decision support in Nigeria.

This article examines the representation of women in post-revolutionary Iranian cinema through close analyses of Jafar Panahi’s The Circle (2000), The
Mirror (1997), and Offside (2006). Moving beyond interpretations that frame Iranian women primarily through censorship and victimhood, the study
argues that Panâhi constructs cinematic environments in which gender emerges as a contested performance shaped by spatial regulation, institutional
control, and everyday negotiation. The analysis is grounded in Stuart Hall’s constructivist theory of representation, Judith Butler’s concept of gender
performativity, and Michel Foucault’s notion of disciplinary power. Through semiotic and spatial analysis of key scenes, the article examines how female
characters navigate regimes of visibility, mobility, and authority within tightly regulated public spaces. Particular attention is given to spatial confinement,
meta-cinematic rupture, and cross-gender disguise as narrative strategies that expose the constructed nature of gender norms. The findings demonstrate
that Panâhi’s films do not merely depict women as passive subjects of ideological control. Instead, they portray female bodies as sites where regulatory
power and performative resistance intersect. By transforming spatial restriction into a cinematic critique of authority, the films reveal how visibility,
movement, and embodiment function as arenas of gendered negotiation. By situating Panâhi’s cinema within feminist film theory and spatial analyses of
power, this study offers a theoretically grounded reassessment of women’s agency in contemporary Iranian cinema. It contributes to broader debates on
representation, visibility, and gendered space.

Semantic technologies and ontologies play an increasing role in scientific workflow systems and knowledge infrastructures. While ontologies are mostly used for the semantic annotation of metadata, semantic technologies enable searching metadata catalogs beyond simple keywords, with some early evidence of semantics used for data translation. However, the next generation of distributed and interdisciplinary knowledge infrastructures will require capabilities beyond simple subsumption reasoning over subclass relations. In this work, we report from the EarthCube Semantics Community by highlighting which role semantics and ontologies should play in the EarthCube knowledge infrastructure. We target the interested domain scientist and, thus, introduce the value proposition of semantic technologies in a non-technical language. Finally, we commit ourselves to some guiding principles for the successful implementation and application of semantic technologies and ontologies within EarthCube.

Over the last 30 years, research methods have shifted from manual, library-based approaches to methods supported by digital tools. Current Large Language Models (LLMs), such as ChatGPT, are no longer relegated to literature search and have expanded into research analysis and knowledge discovery. However, their dependability for conducting meaningful research, especially in specialized, interdisciplinary areas, has not been thoroughly assessed. This study evaluated whether contemporary LLMs can reproduce the research outcomes of a fully documented human study: a 1991 article that identified dermatophytosis (ringworm) in historical fine art. This niche, interdisciplinary topic was selected as a deliberate stress test of LLM capabilities in the research frontier, where crossdomain synthesis and deep domain knowledge are required. Ten commercially available LLMs were systematically tested using two prompt conditions: a basic factual query and a complex motivational prompt designed to elicit human-level research performance. LLM responses were graded on a scale from 0 to 3 based on eight characteristics of the artwork and three factors from the benchmark article. Four categories, which included complete fabrication, misattribution, embellishment, and overclaiming, were used to identify, count, and categorize hallucinations. The original paper, digital collections, and museum databases were all examined as part of the verification process utilized for this classification. Statistical comparisons used the Wilcoxon signed-rank test and Fisher's exact test. No LLM rediscovered any of the seven artworks identified in the original article. 3 out of 10 LLMs (30%) produced incorrect information in response to the simple prompt (M = 0.40, SD = 0.70). 9 of 10 LLMs (90%) produced incorrect information in response to the complex prompt, resulting in 48 total instances (M = 4.80, SD = 4.52). The rise was statistically significant (effect size r = 0.91; Fisher's exact test p = 0.020; Wilcoxon W = 0.0, p = 0.004). Perplexity Pro Deep Research, despite providing the most detailed etiological information (scoring 3 on all three article-level characteristics), also produced the most hallucinations (n = 17). LLMs consistently fabricated plausible-sounding content rather than acknowledging uncertainty. In the specialized interdisciplinary domain tested here, current LLMs proved unreliable as autonomous research agents. Between the two prompt conditions tested, hallucination rates rose twelvefold when the prompt moved from a basic factual query to a complex motivational prompt that explicitly demanded a detailed report. This pattern is consistent with prioritizing output completion above factual accuracy; Reinforcement Learning from Human Feedback (RLHF) is discussed as a plausible explanation for the pattern, but not as a demonstrated mechanism. LLMs can be helpful as research tools when experts in the field use them to verify the results. However, they should not be viewed as independent research agents. It is also Narcross and Marks Biosens. Biomed. 2026, 1(1), 1 2 of 15 relevant for researchers to keep prompts simple and limited in scope to produce more reliable results and to view confident responses with skepticism. Independent verification is necessary.

Modern transportation systems are primarily modeled through geometry, timing optimization, throughput analysis, collision avoidance, and route efficiency. These approaches successfully describe many mechanical properties of transportation systems, yet they incompletely model one of the most important operational characteristics of real traffic environments: traffic possesses emergent behavioral mood. Human drivers continuously evaluate not only distance and velocity, but also collective tension, hesitation, impatience, aggression, instability, and flow predictability across surrounding traffic fields. Drivers adapt behavior in response to recursively evolving environmental pressure generated by other agents operating under shared constraints. This paper proposes that future autonomous transportation systems will likely require some form of mood-sensitive recursive traffic modeling in order to achieve stable large-scale coordination between human and autonomous agents simultaneously. "Mood" here does not refer to literal emotional consciousness within traffic systems. Instead, it refers to distributed behavioral field conditions emerging from recursive multi-agent prediction under environmental and temporal constraints. Traffic mood may therefore be understood as: a dynamically evolving behavioral pressure field governing probabilistic coordination tendencies across a transportation environment. The paper proposes a conceptual architecture for mood-sensitive transportation systems using recursive flow analysis, adaptive signal modulation, behavioral-field inference, and distributed stabilization layers. The purpose is not to replace existing transportation mathematics or engineering models, but to identify an additional coordination layer currently performed naturally by human cognition yet only weakly represented in present autonomous transportation infrastructure.

clude knowledge organization and representation in digital environments, use of semantic web technologies, information retrieval, and foundational issues. Marcondes, Carlos Henrique. Knowledge Organization and Representation in Digital Environments: Relations Between Ontology and Knowledge Organization. Knowledge Organization. 40(2), 115-122. 47 references.

The problem addressed in this work is the persistent separation between parametric memory, encoded within model weights, and non-parametric memory retrieved through external databases or retrieval systems in modern Retrieval-Augmented Generation (RAG) architectures. Although RAG-based systems have improved factual grounding in large language models (LLMs), they introduce architectural fragmentation between the retrieval and generation components, which are often optimized independently and coupled only at inference time. This separation introduces several limitations, including retrieval latency, semantic drift between retrieved evidence and model context, and restricted end-to-end gradient flow between evidence selection and downstream reasoning. Existing memory-augmented architectures partially address these issues but typically maintain retrieval as an external or weakly integrated process.

This article demonstrates that algebra operates exclusively on rational numbers — and that the widespread belief among mainstream mathematics academics that algebra employs irrational numbers, real numbers, or transcendental constants such as π and √2 is a grandiose delusion arising from a fundamental misunderstanding of algebraic symbolism.

Using precise examples, it is shown that whenever an irrational constant such as π or √2 appears in an algebraic expression, the arithmetic operates entirely on the rational coefficients and exponents surrounding the symbol — leaving the symbol itself completely untouched as a placeholder or decorative unit. The expression π = π ÷ 1 is shown to be operationally equivalent to x = x ÷ 1, where x is a rational placeholder and π functions as a physical unit label — never as a genuine arithmetic object.

This observation has immediate and serious consequences for the field axioms of mainstream mathematics — in particular the multiplicative identity axiom, which asserts that a · 1 = a holds universally for all elements of a field including π. Since algebra never actually operates on π but only on its rational coefficients, the multiplicative identity is shown to be a symbol identity rather than a genuine arithmetic truth.

The geometric foundation of these claims is established through georithmetic — the arithmetic of ratios of magnitudes grounded in Thales' proportionality theorem — which operates with complete precision without invoking numbers at all.

This synthetic essay re-presents "Philosophy and Thinking Today" through the lens of the Fourth Industrial Revolution (4IR) and the cognitive hazards of growing formalization. It integrates Dr. Neville Buch's original framework-featuring Merleau-Ponty, the Frankfurt School, Camus, and Hill Collins-with contemporary insights into Cognitive Capitalism, Denoetization, and the "Altar of Autocomplete". The narrative argues that as machine-based routines threaten to modify human consciousness into "passive, dependent, filled" patterns, philosophy must serve as an "intellectual immune system". By utilizing Spiral Historiography and a Pedagogy of Choice, individuals can move from being "anesthetized" consumers of information to "proactive authors" of their own spiritual and intellectual narratives.

Fuzzy reasoning, case-based reasoning (CBR) and experience-based reasoning (EBR) or natural reasoning have been seriously studied for years. However, these studies essentially can be considered as a 1-dimensional approach, because their reasoning paradigm is 1-dimensional. This paper will propose a 2-dimensional (2D) approach that represents fuzzy reasoning, CBR, and EBR in a unified way. This approach also integrates many reasoning paradigms such as abduction, deduction and similarity-based reasoning into a unified treatment. The proposed approach will facilitate research and development of fuzzy reasoning, knowledge/experience management, knowledge-based systems, and CBR.

Resumen: Explicar las causas, los efectos y los sentidos del derecho, reconociendo su parte deóntica e ideológica, implica conceptualizarlo como lenguaje y como un instrumento de comunicación, cuyos fines no se encuentran en el propio discurso del derecho, sino en el político, por más que los grupos hegemónicos, llamados élites o clases dominantes, pretendan ocultarlo, de ahí la importancia de tratarlo como un discurso propio del ejercicio del poder. Prescripciones, matizadas de legalidad y legitimidad, que se imponen como normas, son pena de ser objeto de sanción. Para su estudio se propone la descomposición de la norma en la conducta descrita y en el modalizador deóntico, distinguiendo entre el ser y el deber ser. Complementariamente, se precisan qué son las normas jurídicas, morales y sociales, así como la relación que tienen con el sistema jurídico hegemónico, analizando voces como efectividad, eficacia y eficiencia. En la parte final se propone una Sociología Jurídica, enfocada en el estudio del ejercicio del poder a través del uso del derecho, permitiendo que antes que hablar de desviaciones, crímenes o delitos, debamos referirnos al control social. Palabras clave: usos descriptivo y prescriptivo del lenguaje, sentidos deóntico e ideológico, ejercicio del poder, Sociología del Derecho.

Standardized testing systems increasingly shape access to higher education across the world, yet they are often discussed primarily in terms of fairness, efficiency, or technical validity. This short analytical piece argues that such systems should also be understood as infrastructures that reorganize authority, legitimacy, and educational recognition at national scale.

Using the Scale–Recursion–Erasure (SRE) framework, this short piece analyzes a public announcement poster for Pakistan’s Higher Education Aptitude Test (HAT) system issued by the Higher Education Commission (HEC). The analysis traces how the language of standardization, benchmarking, merit, and psychometric governance constructs a centralized admissions infrastructure that recursively privileges measurable forms of performance across micro, meso, and macro levels of higher education.

The piece further examines what becomes harder for the system to recognize as legitimate, including disciplinary diversity, multilingual educational trajectories, relational pedagogies, and locally grounded forms of knowledge and evaluation. By treating standardized testing as infrastructure rather than simply assessment, the piece contributes to broader discussions on governance, higher education reform, and the politics of educational legitimacy.

This study investigated whether the Reasoning Ways Scale is a valid and reliable teacher measurement tool. The Reasoning Ways Scale was developed by Yalın Uçar et al. (2023). The data of this scale was obtained from 378 pre-service teachers, and the Reasoning Ways Scale consisting of seven sub-dimensions and 21 items, was developed. In this study, for the validity and reliability of the Reasoning Ways Scale for teachers, 520 teachers working in different cities and in different branches in the 2022-2023 academic year were reached by appropriate sampling method. The study data were analyzed using SPSS 25.0 (Statistical Package for Social Sciences). Exploratory and Confirmatory Factor Analyses were conducted for the construct validity of the measurement scale for teachers. As a result of these analyses, it was determined that the instrument had a structure consisting of seven (7) sub-dimensions and 21 items. The reliability coefficients of the sub-dimensions of the measurement tool we...