Search Results (954)

Evaluating risk in complex systems relies heavily on human auditors whose subjective assessments can be compromised by knowledge gaps and varying interpretations. This subjectivity often results in inconsistent risk evaluations, even among auditors examining identical systems, owing to differing pattern recognition processes. In this study, we propose a causality model that can improve the comprehension of risk levels by breaking down the risk factors and creating a layout of risk events and consequences in the system. To do so, the initial step is to define the risk event blocks, each comprising two distinct components: the agent and transfer mechanism. Next, we construct a causal map that outlines all risk event blocks and their logical connections, leading to the final consequential risk. Finally, we assess the overall risk based on the cause-and-effect structure. We conducted real-world illustrative examples comparing risk-level assessments with traditional experience-based auditor judgments to evaluate our proposed model. This new methodology offers several key benefits: it clarifies complex risk factors, reduces reliance on subjective judgment, and helps bridge the gap between subjective and objective uncertainty. The illustrative examples demonstrate the potential value of the model by revealing discrepancies in risk levels compared to traditional assessments. Full article

(1) Background: The development of professional identity in future educators is a dynamic and multifaceted process, shaped by personal experiences, interpersonal relationships, role models, and the values internalized across diverse learning ecologies. This identity formation is closely intertwined with academic achievement, socio-educational integration, peer interactions, and the underlying motivations for choosing a particular educational and professional trajectory. This study explores the connections between students’ educational experiences and their motivation to pursue careers in pedagogy and social education. (2) Methods: Based on 138 autoethnographic narratives written by undergraduate students enrolled in Anthropology of Education courses at two [Spanish] universities. (3) Results: The analysis reveals how reflective engagement with personal educational histories enables students to reconstruct the relational foundations of their learning paths. These reflections inform their academic and career choices, which are understood not as static decisions, but as evolving trajectories shaped by a generational context characterized by uncertainty and change. (4) Conclusions: The findings highlight how students, through their narratives, articulate both their professional aspirations and a vision of the educator as an agent of change—one who emerges in response to, and often in critique of, the educational structures and practices. Full article

With the expansion of offshore oil and gas resources to deepwater areas, the problem of the vortex-induced vibration of marine risers, as a key structure connecting offshore platforms and subsea wellheads, has become increasingly prominent. At present, there are few reviews on the vortex-induced vibration of flexible risers. This review provides a detailed discussion of vortex-induced vibration in marine risers. This review begins with the engineering background. It then systematically analyzes the key factors that influence VIV response. These factors include the riser’s structural parameters, such as aspect ratio and mass ratio. They also include the external fluid environment. Next, this review evaluates current VIV suppression strategies by analyzing specific experimental results. It compares the effectiveness and trade-offs of passive techniques. It also examines the potential and limitations of active methods, which often use smart materials, like piezoelectrics. This study highlights the major challenges in VIV research today. These challenges relate to prediction accuracy and suppression efficiency. Key problems include model uncertainty at high Reynolds numbers and the practical implementation of suppression devices in engineering systems. Finally, this paper presents an outlook on the future directions. It concludes that an intelligent, full-lifecycle integrity management system is the best path forward. Full article

The integration of renewable energy sources (RESs) into power systems, particularly in microgrids, is becoming a prominent trend aimed at reducing dependence on traditional energy sources. Replacing conventional synchronous generators with grid-connected RESs through power electronic converters has significantly reduced the inertia of microgrids. This reduction negatively impacts the dynamics and operational performance of microgrids when confronted with uncertainties, posing challenges to frequency and voltage stability, especially in a standalone operating mode. To address this issue, this research proposes enhancing microgrid stability through frequency control based on virtual inertia (VI). Additionally, the Iterative Learning Control (ILC) method is employed, leveraging iterative learning strategies to improve the quality of output response control. Accordingly, the ILC-VI control method is introduced, integrating the iterative learning mechanism into the virtual inertia controller to simultaneously enhance the system’s inertia and damping coefficient, thereby improving frequency stability under varying operating conditions. The effectiveness of the ILC-VI method is evaluated in comparison with the conventional VI (C-VI) control method through simulations conducted on the MATLAB/Simulink platform. Simulation results demonstrate that the ILC-VI method significantly reduces the frequency nadir, the rate of change of frequency (RoCoF), and steady-state error across iterations, while also enhancing the system’s robustness against substantial variations from renewable energy sources. Furthermore, this study analyzes the effects of varying virtual inertia values, shedding light on their role in influencing response quality and convergence speed. This research underscores the potential of the ILC-VI control method in providing effective support for low-inertia microgrids. Full article

We live in an era where digitalization and omnichannel strategies significantly transform retail landscapes, and accurate spatial analytics from Geographic Information Systems (GIS) can deliver substantial competitive benefits. Nonetheless, despite evident practical advantages for specific targeting strategies and operational efficiency, the degree of GIS integration into academic marketing literature remains ambiguous. Clarifying this uncertainty is beneficial for advancing theoretical understanding and ensuring retail strategies fully leverage robust, data-driven spatial intelligence. To examine the intellectual development of the field, co-occurrence analysis, topic mapping, and citation structure visualization were performed on 4952 peer-reviewed articles using the Bibliometrix R package (version 4.3.3) within R software (version 4.4.1). The results demonstrate that although GIS-based methods have been effectively incorporated into fields like site selection and spatial segmentation, traditional marketing research has not yet entirely adopted them. One of the study’s key findings is the distinction between “author keywords” and “keywords plus,” where researchers concentrate on novel topics like omnichannel retail, artificial intelligence, and logistics. However, “Keywords plus” still refers to more traditional terms such as pricing, customer satisfaction, and consumer behavior. This discrepancy presents a misalignment between current research trends and indexed classification practices. Although the mainstream retail research lacks terminology connected to geomarketing, a theme evolution analysis reveals a growing focus on technology-driven and sustainability-related concepts associated with the Retail 4.0 and 5.0 paradigms. These findings underscore a conceptual and structural deficiency in the literature and indicate the necessity for enhanced integration of GIS and spatial decision support systems (SDSS) in retail marketing. Full article

Maritime transportation is the backbone of global trade, with ports acting as pivotal nodes for the efficient and resilient movement of goods in international supply chains. However, most existing studies lack a systematic and integrated framework for assessing port connectivity. To address this gap, this study develops an integrated Bayesian Network (BN) modeling approach that, for the first time, simultaneously incorporates international connectivity, port competitiveness, and hinterland connectivity within a unified probabilistic framework. Drawing on empirical data from 26 major coastal countries in Asia, the model quantifies the multi-layered and interdependent determinants of port connectivity. The results demonstrate that port competitiveness and hinterland connectivity are the dominant drivers, while the impact of international shipping links is comparatively limited in the current Asian context. Sensitivity analysis further highlights the critical roles of rail transport development and trade facilitation in enhancing port connectivity. The proposed BN framework supports comprehensive scenario analysis under uncertainty and offers targeted, practical policy recommendations for port authorities and regional planners. By systematically capturing the interactions among maritime, port, and inland factors, this study advances both the theoretical understanding and practical management of port connectivity. Full article

Graph theory models relationships by representing entities as vertices and their interactionsas edges. To handle directionality and multiple head–tail assignments, various extensions—directed, bidirected, and multidirected graphs—have been introduced, with the multidirected graph unifying the first two. In this work, we further enrich this landscape by proposing the Multidirected hypergraph, which merges the flexibility of hypergraphs and superhypergraphs to describe higher-order and hierarchical connections. Building on this, we introduce five uncertainty-aware Multidirected frameworks—fuzzy, neutrosophic, plithogenic, rough, and soft multidirected graphs—by embedding classical uncertainty models into the Multidirected setting. We outline their formal definitions, examine key structural properties, and illustrate each with examples, thereby laying groundwork for future advances in uncertain graph analysis and decision-making. Full article

The presence of hope significantly influences how youth interpret possibilities and commit to future-oriented action. This qualitative study investigates how fifteen Black emerging adults, ages eighteen to twenty-five, living in a major United States urban city on the East Coast, describe their aspirations, goal-setting strategies, and responses to personal and structural challenges. Participants were categorized as connected or disconnected based on their engagement in school, work, or training programs. Using Reflexive Thematic Analysis of interviews, the research identified key differences in agency, emotional orientation, and access to guidance between the two groups. Connected participants often described clear, structured goals supported by networks of mentorship and opportunity. Disconnected participants expressed meaningful hope, yet described fewer supports and greater uncertainty in achieving their goals. These findings highlight how consistent exposure to guidance and structured environments strengthens future orientation and internal motivation. These results deepen our understanding of how young people experience hope across diverse contexts and show that mentorship, intentional goal setting, and greater access to opportunity play a vital role in sustaining hopeful thinking during the transition to adulthood. Full article

We explore the realm of uncertainty theory by investigating diverse notions of convergence and statistical convergence concerning complex uncertain sequences. Complex uncertain variables can be described as measurable functions mapping from an uncertainty space to the set of complex numbers. They are employed to represent and model complex uncertain quantities. We introduce the concept of lacunary almost statistical convergence of order $\alpha$$(0<\alpha \le 1)$ for complex uncertain sequences, examining various aspects of uncertainty such as distribution, mean, measure, uniformly almost sure convergence and almost sure convergence. Additionally, we establish connections between the constructed sequence spaces by providing illustrative instances. Importantly, lacunary almost statistical convergence provides a flexible framework for handling sequences with irregular behavior, which often arise in uncertain environments with imprecise data. This makes our approach particularly useful in practical fields such as engineering, data modeling and decision-making, where traditional deterministic methods are not always applicable. Our approach offers a more flexible and realistic framework for approximating functions in uncertain environments where classical convergence may not apply. Thus, this study contributes to approximation theory by extending its tools to settings involving imprecise or noisy data. Full article

This paper introduces a framework of hypercompositional algebra on fuzzy graphs by defining and analyzing fuzzy path-based hyperoperations. Building on the notion of strongest strong paths (paths that are both strength-optimal and composed exclusively of strong edges, where each edge achieves maximum connection strength between its endpoints), we define two operations: a vertex-based fuzzy path hyperoperation and an edge-based variant. These operations generalize classical graph hyperoperations to the fuzzy setting while maintaining compatibility with the underlying topology. We prove that the vertex fuzzy path hyperoperation is associative, forming a fuzzy hypersemigroup, and establish additional properties such as reflexivity and monotonicity with respect to $\alpha$-cuts. Structural features such as fuzzy strong cut vertices and edges are examined, and a fuzzy distance function is introduced to quantify directional connectivity strength. We define an equivalence relation based on mutual full-strength reachability and construct a quotient fuzzy graph that reflects maximal closed substructures under the vertex fuzzy path hyperoperation. Applications are discussed in domains such as trust networks, biological systems, and uncertainty-aware communications. This work aims to lay the algebraic foundations for further exploration of fuzzy hyperstructures that support modeling, analysis, and decision-making in systems governed by partial and asymmetric relationships. Full article

Thermal barrier coatings have been widely used in industrial fields where thermal damage occurs, and they are crucial for insulation technology and for the safe service of high-temperature components. So, it is critical to accurately predict the reliability of thermal barrier coatings. In this work, an adaptive reliability analysis method based on radial basis functions is proposed, in which different shape parameters and subsets are used to initiate different radial basis function models for multiple predictions. An active learning function that comprehensively considers local uncertainty, limit state function information, and distance among samples is then used for sequential sampling, and the proposed method is validated via a four-branch series connection system. Finally, a reliability analysis is conducted on the failure of interface oxidation in thermal barrier coatings, which verifies the feasibility of the proposed method. Full article

Background: It is generally well-known that narration of care is critically important to high-quality nursing care. Narration of care is loosely defined as a nurse’s ability to describe to patients and families the clinical purpose behind nursing practice, what is hoped to be achieved, and the “why” (or clinical rationale) behind nursing activities. Despite the importance of narration of care, there is little practical guidance given to nurses about how to narrate care—what makes for effective or ineffective narration of care. Objective: Our aim was to develop a framework for teaching nurses and patient care assistants (PCAs) on how to effectively narrate care. In this article, we provide a practical framework for teaching nurses and PCAs how to narrate care. We describe the process of developing the framework as part of quality improvement efforts and implementing a course for eight hospitals based on the framework. Methods: Consistent with a Plan-Do-Study Act (PDSA) quality improvement approach, we developed the framework by first conducting a data and literature review, then convening a taskforce, discussing with patients on our existing committees, and finally formulating a framework. We then drafted supplementary cases and course material and implemented a course to teach nurses and PCAs how to narrate care. Results: The narration of care framework (NOC) that we developed and implemented consisted of the following five principles, which can be called RECAP as an acronym: 1. The “R” in RECAP stands for removing uncertainty. 2. The “E” in RECAP stands for explaining the environment. 3. The “C” in RECAP stands for being calm and sincere. 4. The “A” in RECAP stands for assume nothing. 5. The “P” in RECAP stands for personal connection. As for the course developed based on the RECAP principles, there was a total of 276 course offerings conducted by 30 facilitators, and 7341 nurses and PCAs completed the course. The evaluations reflected that 99% of learners believed their learning was improved by the course. Discussion: There are several multifaceted benefits to NOC: nurses’ and PCAs’ capability to narrate care well shows empathy and compassion to patients; it strengthens patient understanding and education that can lead to improved patient outcomes; and it helps allay patients’ uncertainties and anxieties. In essence, narrating care in an effective manner cultivates a strong nurse–patient therapeutic relationship. Yet, in the absence of any practical guidance, nurses and PCAs are left to develop narration skills on their own, learning by trial and error, and, in doing so, perhaps failing to meet patients’ needs and failing to fully derive the many benefits that the NOC is designed to achieve. Our hope is that, if hospital systems adopt our work, nurses and PCAs can comfortably and confidently enter the profession knowing the purpose or narrating care, its many benefits, and how to practically conduct sufficient narration, and what would constitute insufficient narration. Hospitals, in turn, can specify and clearly articulate their expectations for nurses and PCAs narrating with patients—what would make for a strong, compassionate process and what would be inadequate. For more experienced nurses, they can use the RECAP framework to reflect on their own practices and perhaps strengthen or refreshen existing skills. Conclusions: NOC is acknowledged, somewhat implicitly, as being critical to nursing and PCA practice, yet practical instruction and specified principles are lacking. We aimed to fill this gap by developing, implementing, and teaching a practical framework, armed with many tools nurses can use. Full article

The COVID-19 pandemic sparked changes globally, as leaders scrambled to protect wellbeing and safety. With many U.S. students sent away from their campuses, undergraduate students still grappled with the time-old question: “what will I do after college,” except during an unprecedented time in history rife with heightened career uncertainty. This qualitative study presents the results of a survey administered as part of a mind–body health project conducted in the wake of the pandemic, speaking directly to undergraduate college students’ health-related career aspirations. Two open-ended survey questions—(1) what is your intended career, and (2) how (if at all) has the COVID-19 pandemic changed your perspective about your future career—were administered with thematic analysis conducted. Qualitative analysis using hybrid data and theory-driven approaches revealed several themes around an increased desire to work within health-related fields, decreased desire to work in healthcare, non-medical to medical career shift, and additional undecidedness. Connecting theory to practice, Super’s Life-Space, Life-Span Career Theory and Krumboltz’s Social Learning Theory of Career Decision-Making guide practical implications and grander discussion around career development during periods of crisis. Full article

Aiming at the problems of frequent voltage overruns in distribution networks and difficulties in centralized optimal dispatch due to the uncertainties of distributed renewable energy sources and bus loads, this paper proposes a dynamic cluster voltage control method considering power deficit and resource allocation in an active distribution network. First, the modularity index is constructed by considering the ability of the bus electrical coupling, and the voltage regulation resources are allocated by balancing power compensation capacity and physical connectivity. This method competes with cluster partitioning and selects pilot buses. Then, an active and reactive power coordinated control model based on non-dominated sorting genetic algorithm II (NSGA-II) is developed. The model aims to minimize voltage violations, distribution network losses, and power consumption costs. Finally, five representative control scenarios are simulated and compared on an enhanced IEEE 51 bus distribution network. The results show that the proposed strategy effectively mitigates node voltage violations, reduces the losses, and enhances resource efficiency. Full article

Background: In today’s rapidly evolving business environment, organizational agility (OA) has become increasingly critical for companies to maintain competitiveness and sustainability. Business intelligence (BI) is pivotal in enabling organizational agility by providing the necessary tools and insights to navigate uncertainties and capitalize on opportunities. This study aimed to investigate the relationship between BI and organizational agility, particularly within the pharmaceutical manufacturing sector in the Middle East and North Africa (MENA) region. The systematic literature review followed Kitchenham’s guidelines, which was supplemented with a VOS analysis to visualize the interconnectedness of BI and organizational agility. The analysis revealed a direct relationship between BI and organizational agility, with the critical variables of innovation, competitive advantage, firm performance, and dynamic capabilities influencing this connection. The MENA region shows promise in contributing to this field, but further research is needed. Leveraging BI capabilities can enhance organizational agility, positioning companies for sustained success amidst uncertainty. Addressing challenges and fostering a supportive organizational culture is essential for realizing the full potential of BI-driven agility. This study makes an original and timely contribution by examining the relationship between business intelligence (BI) and organizational agility (OA) through a systematic literature review across multiple countries. The study focuses specifically on the Middle East and North Africa (MENA) region, which has received insufficient attention in previous research. Unlike previous studies that focus on isolated cases, this work combines bibliometric analysis with a structured review methodology. It provides a clear summary of how BI supports key outcomes such as innovation, dynamic capabilities, and competitive advantage Full article