Search Results (685)

The purpose of this article is to introduce the concept of elliptic-valued suprametric spaces and to establish some common fixed point theorems within this newly proposed framework. The development of elliptic-valued suprametric spaces, along with the main results presented here, is illustrated through non-trivial examples. As applications, we employ our fixed point results to study the nonlinear Volterra integral equation of the second kind, demonstrating the existence and uniqueness of solutions under suitable conditions. In particular, we highlight the role of such equations in age-structured population models, where they serve as powerful tools for describing hereditary effects, density-dependent interactions, and delayed responses in population dynamics. This connection bridges the abstract theory with applied contexts in mathematical biology, ecology, and epidemiology, emphasizing the relevance of elliptic-valued suprametric structures in both theoretical analysis and real-world applications. Furthermore, we derive corresponding fixed point results in elliptic-valued suprametric spaces, complex-valued suprametric spaces, elliptic-valued metric spaces, and complex-valued metric spaces as corollaries of our main findings. Full article

The education field has been striving to develop STEM teaching and learning methodologies that effectively integrate subject knowledge across disciplines and connect it to daily life. Many teachers believe that practical work can help students better grasp abstract concepts. However, they often hesitate to incorporate practical work due to constraints, such as limited resources and a lack of experimental skills among students. As a result, demonstrations are frequently used as an alternative. This study presents the findings of a systematic literature review conducted in accordance with PRISMA guidelines, analyzing the advantages, disadvantages, and potential enhancements of using the demonstration method in STEM education. After examining 49 relevant studies, this review identified 15 benefits and 14 challenges associated with the demonstration method, encompassing their impact on students, teachers, and operational aspects. Additionally, six key components were discovered that enhance the efficacy of the demonstration method. Based on the findings, recommendations are proposed for policymakers, universities, and schools to improve the implementation and outcomes of demonstration-based teaching and learning in STEM education. Full article

Previous studies, constrained by the overly rigid stability requirements, often fail to adapt to complex systems and struggle to identify stable outcomes that align with the practical context of multi-agent resource allocation. To address the three-sided matching problem in complex socio-technical and business management systems, this paper proposes a fuzzy stable matching method for three-sided agents under a framework of combinatorial preference relations, integrating network and decision theory. First, we construct a membership function to measure the degree of preference satisfaction between elements of different agents, and then define the concept of fuzzy stability. By incorporating preference satisfaction, we introduce the notion of fuzzy blocking strength and derive the generation conditions for blocking triples and fuzzy stability under the fuzzy stable criterion. Furthermore, we abstract the three-sided matching problem with combined preference relations into a shortest path problem. Second, we prove the equivalence between the shortest path solution and the stable matching outcome. We adopt Dijkstra’s algorithm for problem-solving and derive the time complexity of the algorithm under the pruning strategy. Finally, we apply the proposed model and algorithm to a case study of project assignment in software companies, thereby verifying the feasibility and effectiveness of this three-sided matching method. Compared with existing approaches, the fuzzy stable matching method developed in this study demonstrates distinct advantages in handling preference uncertainty and system complexity. It provides a more universal theoretical tool and computational approach for solving flexible resource allocation problems prevalent in real-world scenarios. Full article

The clinical management of major depressive disorder is constrained by a trial-and-error approach. The clinical management of major depressive disorder is constrained by a trial-and-error approach. While computational methods have focused on static binary classification (e.g., responder vs. non-responder), they ignore the dynamic nature of recovery. Building upon the recently proposed prognostic theory of treatment response, this article presents a methodological framework for its operationalisation. We define a multi-modal data architecture for the theory’s core constructs—the Patient State Vector (PSV), Therapeutic Impulse Function (TIF), and Predicted Recovery Trajectory (PRT)—transforming them from abstract concepts into specified computational inputs. To model the asynchronous interactions between these components, we specify a Time-Aware Long Short-Term Memory (LSTM) architecture, providing explicit mathematical formulations for time-decay gates to handle irregular clinical sampling. Furthermore, we outline a synthetic validation protocol to benchmark this dynamic approach against static baselines. By integrating these technical specifications with a translational pipeline for Explainable AI (XAI) and ethical governance, this paper provides the necessary blueprint to transition psychiatry from theoretical prognosis to empirical forecasting. Full article

Background: Emerging evidence suggests that lipedema may share hormonal, inflammatory, and genetic mechanisms with gynecologic diseases, particularly endometriosis. However, the extent and nature of these interrelationships remain poorly characterized, supporting the need for this scoping review. Objectives: To map and synthesize the available evidence on the clinical, pathophysiological, and epidemiological interrelationships between lipedema in women, endometriosis, and other gynecologic diseases. Methods: Searches were conducted in international and regional health databases, including MEDLINE (PubMed), CINAHL, Scopus, Embase, Web of Science, the Cochrane Library, LILACS/VHL, APA PsycInfo, SciELO, Epistemonikos, and La Referencia, as well as grey literature sources and relevant institutional websites. There were no language restrictions. The search period began in 1940, the year in which lipedema was first described by Allen and Hines. Study selection followed a two-stage process conducted independently by two reviewers, consisting of title and abstract screening followed by full-text review. Data extraction was performed using a pre-developed and peer-reviewed instrument covering participants, concept, context, study methods, and main findings. The review protocol was registered in the Open Science Framework. Results: Twenty-five studies from ten countries were included. Synthesized evidence supports the characterization of lipedema as a systemic condition with metabolic and hormonal dimensions. Key findings include symptom onset linked to reproductive milestones, a high frequency of gynecologic and endocrine comorbidities, and molecular features overlapping with steroid-dependent pathologies. These patterns reflect a recent shift from a predominantly lymphovascular paradigm toward a more integrated endocrinometabolic framework. Conclusions: The findings indicate that lipedema clusters with hormone-sensitive gynecologic and endocrine features across reproductive life stages. Full article

Many rural communities are struggling to understand the changing climate and how to mitigate and adapt to its negative effects. “Climate literacy” (i.e., an understanding of the climate system, how human actions influence it, and how it affects society and the Earth) may be a necessary precursor to climate action (i.e., steps that help to mitigate or adapt to climate change). For rural communities in the Brazilian Amazon, where access to formal education is limited, grasping abstract concepts like greenhouse gas emissions can be particularly challenging. We asked: Is climate literacy a necessary precursor to climate action? We conducted 22 semi-structured interviews with forest extractivists living within the Chico Mendes Extractive Reserve in the state of Acre, Brazil. We found that forest extractivists are experiencing the impacts of climate change but lack an understanding of its causes and forms of mitigation and are unaware of ways to adapt to it. Improved educational opportunities could support both climate literacy and, in turn, climate action. Full article

Experimental prints made by Jackson Pollock in Stanley William Hayter’s Atelier 17 in 1944–45 were crucial to the evolution of his modernist style, an evolution quite different from Clement Greenberg’s conception of it. Hayter said “Pollock always claimed that he had two masters, Benton and me.” Following Charles Darwent’s Surrealists in New York: Atelier 17 and the Birth of Abstract Expressionism 2023 and Christina Weyl’s The Women of Atelier 17 2019, this article examines a 1944–45 engraving in which Pollock inscribed the letters A, R, T. This examination reveals the experimental techniques and the gendered themes that shaped Pollock’s continued exploration of his art as erotic dialogue. Absorbing Hayter’s technical understanding of the three-dimensionality of an engraved line as it produced and moved through “the space of the imagination,” Pollock succeeded in mediating between male and female tensions, stated in underlying imagery, as he began in ‘ART’ to generate his abstract and unifying all-over linear webs, culminating in such works as Autumn Rhythm 1950. Full article

This paper does not aim to prove new mathematical theorems or claim a fundamental unification of physics and information, but rather to provide a new pedagogical framework for interpreting foundational results in algorithmic information theory. Our focus is on understanding the profound connection between entropy and Kolmogorov complexity. We achieve this by applying these concepts to a physical model. Our work is centered on the distinction, first articulated by Boltzmann, between observable low-complexity macrostates and unobservable high-complexity microstates. We re-examine the known relationships linking complexity and probability, as detailed in works like Li and Vitányi’s An Introduction to Kolmogorov Complexity and Its Applications. Our contribution is to explicitly identify the abstract complexity of a probability distribution $\mathrm{K}\left(\rho \right)$ with the concrete physical complexity of a macrostate $\mathrm{K}\left(M\right)$. Using this framework, we explore the “Not Alone” principle, which states that a high-complexity microstate must belong to a large cluster of peers sharing the same simple properties. We show how this result is a natural consequence of our physical framework, thus providing a clear intuitive model for understanding how algorithmic information imposes structural constraints on physical systems. We end by exploring concrete properties in physics, resolving a few apparent paradoxes, and revealing how these laws are the statistical consequences of simple rules. Full article

The deployment of autonomous systems in human environments demands sophisticated mechanisms for recognizing and preventing harm. This paper proposes an innovative discovery method for identifying harm-relevant features through the systematic analysis of thick harm verbs—semantically and pragmatically rich linguistic concepts like “puncture”, “crush”, or “poison” that encode both the mechanics and normative evaluations of specific harm types. By analyzing thick harm verbs to extract the information they encode, we can systematically identify the objects, properties, mechanisms, and contextual conditions that autonomous systems need to track to recognize and prevent harm. We demonstrate how this discovery method can be implemented with the support of large language models as analytical assistance tools, showing how human analysts can operationalize the framework with current technology. The resulting feature specifications discovered through this method provide foundations for constructing harm ontologies that bridge abstract ethical principles and concrete system requirements, addressing a critical gap in autonomous systems design while maintaining explanatory transparency essential for safe deployment in human environments. Full article

Incivility and civility have been studied for more than a century across disciplines and in many areas ranging from workplaces to communication, the digital world, and everyday life. They are often used to the detriment of marginalized groups. Their negative use is seen to set the groundwork for other negative treatments, such as bullying and harassment, impacting the social climate in a negative way. Ostracism is seen to be linked to incivility. Disabled people disproportionally face negative treatments, such as bullying and harassment, and experience a negative social climate, as highlighted by the UN Convention on the Rights of People with Disabilities, suggesting that they also disproportionately experience incivility and ostracism. Climate surveys aim to expose toxic social climate in workplaces, schools, and communities caused by incivility, ostracism, bullying, and harassment. As such, how incivility, civility, ostracism, and the design of climate surveys are discussed in the literature is of importance to disabled people. We could find no review that analyzed the use of climate surveys beyond individual surveys and the concepts of incivility and ostracism in relation to disabled people. The objective of our study was to contribute to filling this gap by analyzing the academic literature present in SCOPUS, EBSCO HOST (70 databases), and Web of Science, performing keyword frequency and content analysis of abstracts and full texts. Our findings provide empirical evidence for a systemic neglect of disabled people in the topics covered: from 21,215 abstracts mentioning “civilit*” or “incivilit*”, only 14 were relevant, and of the 8358 abstracts mentioning ostracism, only 26 were relevant. Of the 3643 abstracts mentioning “climate surveys,” 12 sources covered disabled people by focusing on a given survey, but not one study performed an evaluation of the utility of climate surveys for disabled people in general. Racism is seen as a structural problem facilitating civility/incivility. Ableism, the negative judgments of a given set of abilities someone has, and disablism, the systemic discrimination based on such judgments, are structural problems experienced by disabled people, facilitating civility/incivility. However, ableism generated only 2 hits, and disablism/disableism had no hits. Most of our sources focused on workplace incivility, and authors were mostly from the USA. We found no linkage to social and policy discourses that aim to make the social environment better, such as equity, diversity, and inclusion, well-being, and science and technology governance. This is the first paper of its kind to look in depth at how the academic literature engages with the concepts of civility, incivility, and ostracism and with the instrument of social climate surveys in relation to disabled people. Our findings can be used by many different disciplines and fields to strengthen the theoretical and practical discussions on the topics in relation to disabled people and beyond. Full article

Background/Objectives: Unmet healthcare needs, driven by structural and patient-level barriers, are particularly critical in chronic obstructive pulmonary disease (COPD). However, limited research has examined how academic themes on this topic connect and evolve over time. This study analyzed the structure and temporal shifts in research trends on unmet healthcare needs in COPD to identify key concepts and topics and policy implications. Methods: We systematically searched PubMed, Embase, and CINAHL (12–15 March 2025) to identify English-language abstracts on unmet healthcare needs in COPD. Eligible studies were peer-reviewed articles with an English-language abstract that examined unmet healthcare needs from the patient perspective. In total, 451 abstracts were analyzed using text network analysis and Latent Dirichlet Allocation. Topic distributions before and after the coronavirus disease pandemic were assessed using chi-square tests, and findings were interpreted within Penchansky and Thomas’s 5A healthcare access framework. Results: Six topics emerged: socioeconomic disparities, early diagnosis and symptom management, guideline-based information and technology use, integrated care for advanced COPD, access to pulmonary rehabilitation, and equitable medication availability. These topics mapped onto all five access dimensions, underscoring the multidimensional nature of unmet healthcare needs. Network analysis identified management, diagnosis, symptoms, exacerbation, and other related terms as central hubs in the discourse. Post-pandemic, research shifted toward digital information delivery, technology adoption, and equitable pharmacotherapy. Conclusions: Findings suggest that reducing unmet healthcare needs in COPD requires integrated systems that address both disease complexity and access barriers. Targeted, multidisciplinary, and policy-driven interventions in highly central domains are needed to reduce disparities and improve outcomes. This study also confirmed a post-pandemic shift in research priorities, emphasizing the need for equitable and adaptive healthcare policies. Full article

The Discrete Event System Specification (DEVS) formalism provides a mathematical foundation for modeling hierarchical discrete-event systems. However, the Depth-First Search (DFS) scheduling used in the classical DEVS abstract simulator conflicts with the concurrency semantics of Hardware Description Language (HDL) simulators such as Verilog or VHDL. This mismatch induces timing distortions, including pipeline skew and zero-time feedback loops. To address these limitations, this study proposes a new DEVS simulation kernel that adopts Breadth-First Search (BFS) scheduling, integrating the delta-round concept. This approach employs an event-parking mechanism that separates event computation from application, structurally aligning with HDL’s Active–NBA–Reactive phases and enabling semantically simultaneous updates without introducing additional ε-time. Case studies demonstrate that the proposed BFS-based DEVS kernel eliminates timing discrepancies in pipeline and feedback-loop structures and establishes a formal foundation for semantic alignment between DEVS and HDL simulators. Full article

It is hard to envision a modern world where information technology does not facilitate daily tasks, including learning and teaching. This paper explores the use of virtual reality (VR) simulations in chemistry education, focusing on how immersive VR environments can enhance the learning experience for students. With chemistry often posing challenges due to its abstract and complex concepts, VR technology allows for a more interactive and visual approach, enabling students to visualize molecular structures, chemical reactions, and laboratory procedures. The study concludes that virtual reality (VR) simulations are crucial in modernizing chemistry education by making abstract and complex concepts more interactive and visual. Through a comprehensive analysis of current VR tools and simulations, the article discusses their strengths and limitations, providing a critical overview of the role of VR in modernizing chemistry education. The findings suggest that VR simulations can significantly improve students’ engagement with and understanding of complex chemistry concepts. Also, the results suggests that integrating VR into chemistry education can revolutionize traditional teaching methods, providing a more immersive and engaging learning experience. Full article

Technology plays an increasingly vital role in modern education, providing new opportunities to enhance engagement and conceptual understanding. Among emerging innovations, Augmented Reality (AR) enables interactive visualization that supports deeper comprehension of abstract and spatially complex concepts. This study aimed to evaluate the impact of AR technology integrated with the STEAM approach on fifth-grade students’ learning of geometric solids, focusing on spatial skills, motivation, and academic achievement. A quasi-experimental design was implemented, involving an experimental group that engaged in AR- and STEAM-based activities and a control group that followed traditional instruction. Results indicated significant improvement in geometry test performance within the experimental group (p < 0.001) and higher post-test performance compared to the control group (p = 0.005). Although motivation scores were higher in the experimental group, the difference was not statistically significant (p = 0.083), suggesting a positive trend that merits further exploration with a larger sample. Overall, the findings highlight the pedagogical potential of integrating AR and STEAM approaches to support engagement and conceptual understanding in geometry education. Full article

Graph generalization is a powerful concept with a wide range of potential applications, while established algorithms exist for generalizing simple graphs, practical approaches for more complex graphs remain elusive. We introduce a novel formal model and algorithm (GGA) that generalizes labeled directed graphs without assuming label identity. We evaluate GGA by focusing on its information preservation relative to its input graphs, its scalability in execution, and its utility for three applications: abstract syntax trees, class graphs, and call graphs. Our findings reveal the superiority of GGA over alternative tools. GGA outperforms ASGard by an average of 5–18% on metrics related to information preservation; GGA matches 100% with diffsitter, indicating the correctness of the output. For class graphs, GGA achieves 77.1% in precision at 5, while for call graphs, it exhibits 60% in precision at 5 for a specific application problem. We also test performance for the first two applications: GGA’s execution time scales linearly with respect to the product of vertex count and edge count. Our research demonstrates the ability of GGA to preserve information in diverse applications while performing efficiently, signaling its potential to advance the field. Full article