Search Results (221)

Ontologies are essential tools for representing, organizing, and sharing knowledge across various domains. This study presents a methodology for ontology construction supported by large language models (LLMs), with an initial application in the automotive sector. Specifically, a user preference ontology for adaptive interfaces in autonomous machines was developed using ChatGPT-4o. Based on this case study, the results were generalized into a reusable methodology. The proposed workflow integrates classical ontology engineering methodologies with the generative and analytical capabilities of LLMs. Each phase follows well-established steps: domain definition, term elicitation, class hierarchy construction, property specification, formalization, population, and validation. A key innovation of this approach is the use of a guiding table that translates domain knowledge into structured prompts, ensuring consistency across iterative interactions with the LLM. Human experts play a continuous role throughout the process, refining definitions, resolving ambiguities, and validating outputs. The ontology was evaluated in terms of logical consistency, structural properties, semantic accuracy, and inferential completeness, confirming its correctness and coherence. Additional validation through SPARQL queries demonstrated its reasoning capabilities. This methodology is generalizable to other domains, if domain experts adapt the guiding table to the specific context. Despite the support provided by LLMs, domain expertise remains essential to guarantee conceptual rigor and practical relevance. Full article

Bayesian methods have attracted increasing interest in the design and analysis of clinical trials. Many of these clinical trials investigate time-to-event endpoints. The Weibull distribution is often used in survival and reliability analysis to model time-to-event data. We propose a process to elicit information about the parameters of the Weibull distribution for pharmaceutical applications. Our method is based on an expert’s answers to questions about the median and upper quartile of the distribution. Using the elicited information, a joint prior is constructed for the median and upper quartile of the Weibull distribution, which induces a joint prior distribution on the shape and rate parameters of the Weibull. To illustrate, we apply our elicitation methodology to a pediatric clinical trial, where information is elicited from a subject-matter expert for the control arm. Full article

Climate change is projected to increase the intensity and frequency of natural hazards such as heat waves, extreme rainfall, heavy snowfall, typhoons, droughts, floods, and cold waves, potentially impacting the operational safety of critical infrastructure, including nuclear power plants (NPPs). Although quantitative indicators exist to screen-out natural hazards at NPPs, comprehensive methodologies for assessing climate-related hazards remain underdeveloped. Furthermore, given the variability and uncertainty of climate change, it is realistically and resource-wise difficult to evaluate all potential risks quantitatively. Using a structured expert elicitation approach, this study systematically identifies and prioritizes climate-related natural hazards for Korean NPPs. An iterative Delphi survey involving 42 experts with extensive experience in nuclear safety and systems was conducted and also evaluated using the best–worst scaling (BWS) method for cross-validation to enhance the robustness of the Delphi priorities. Both methodologies identified extreme rainfall, typhoons, marine organisms, forest fires, and lightning as the top five hazards. The findings provide critical insights for climate resilience planning, inform vulnerability assessments, and support regulatory policy development to mitigate climate-induced risks to Korean nuclear power plants. Full article

Bayesian networks (BNs) are popular models that represent complex relationships among variables. In the discrete case, these relationships can be quantified by conditional probability tables (CPTs). CPTs can be derived from data, but if data are not sufficient, experts can be involved to assess the probabilities in the CPTs through Structured Expert Judgment (SEJ). This is often a burdensome task due to the large number of probabilities that need to be assessed and the structured protocols that need to be followed. To lighten the elicitation burden, several methods have previously been developed to construct CPTs using a limited number of input parameters, such as InterBeta, the Ranked Nodes Method (RNM), and Functional Interpolation. In this study, the burden/accuracy trade-off of InterBeta is researched by applying the method to reconstruct previously elicited CPTs and simulated CPTs, first by comparing these CPTs to ones constructed using RNM and Functional Interpolation. After that, InterBeta extensions are proposed and tested, including an extra mean function (shifted geometric mean), the elicitation of additional middle rows, and the newly proposed extension ExtraBeta. InterBeta with parent weights is found to be the best-performing method, and the ExtraBeta extension is found to be promising and is proposed for further exploration. Full article

Power grid infrastructures, essential to modern societies for electricity distribution, are prone to vulnerabilities due to their numerous sensitive components, necessitating a comprehensive risk assessment. Uncertainty in historical failure data often compromises accurate risk quantification, leading to the integration of expert elicitation as a solution. This study develops a Bayesian network (BN) risk assessment model integrated with fuzzy set theory (FST), referred to as the fuzzy Bayesian network (FBN). By incorporating expert insights, this model quantifies internal and external risk variables more comprehensively. Crisp probabilities (CPr), derived from regional transmission operator (RTO) failure incident data, are complemented by fuzzy probabilities (FPr) from expert elicitation. The findings indicate that equipment conditions, specifically transmission lines and circuit breakers, are critical threats to power grids. Environmental factors, particularly storms, emerge as vulnerability risks. A comparison of results using both CPr plus FPr versus FPr alone underscores the utility of expert elicitation in risk assessment. This research demonstrates the effectiveness of FBNs through expert elicitation, providing a comprehensive and accurate framework for power grid risk assessment. To improve risk evaluation in critical infrastructure, integrated data collection techniques are recommended. Full article

African swine fever (ASF), a viral hemorrhagic disease with exceptionally high lethality in domestic pigs and Eurasian wild boar, reached Germany in 2020, with the confirmation of the first case in a wild boar next to the border to Poland. Since then, 6621 cases in wild boar but only 19 outbreaks in domestic pigs were confirmed. Biosecurity is crucial in preventing the infection of domestic pig holdings. Already in 2019, an online assessment tool, the so-called “ASP-Risikoampel” (ASF risk traffic light), was launched. It enables farms to identify ASF-specific weaknesses and take targeted measures to minimize risks/optimize the biosecurity standard anonymously and free of charge. The development of the tool incorporating expert opinion elicitation in a Delphi process is detailed and the results of 2290 self-assessments of farms between 2019 and 2023 are evaluated. The proportion of tool utilization relative to the average number of holdings in Germany in this time span was 11.9% with marked differences between the federal states. Most of the farms achieved biosecurity scores above 66.7%, qualifying for a “green traffic light”. The results were significantly different among the federal states. The best performing states were those with the largest mean farm size. The latter was significantly correlated with performance on the farm level. Full article

Under extreme operating conditions such as high temperatures, strong corrosion, and cyclic thermal shocks, key equipment in solar tower power plants (STPPs) is prone to severe accidents and results in significant losses. To systematically quantify potential failure risks and address the methodological gaps in existing research, this study proposes a risk assessment framework combining a novel scenario propagation model covering triggering factors, precursor events, accident scenarios, and response measures with an interval type-2 fuzzy set (IT2FS) Bayesian network. This framework establishes equipment failure evolution pathways and consequence evaluation criteria. To address data scarcity, the methodology integrates actual case data and expert elicitation to obtain assessment parameters. Specifically, an IT2FS-based similarity aggregation method quantifies expert opinions for prior probability estimation. Additionally, to reduce computational complexity and enhance reliability in conditional probability acquisition, the IT2FS-integrated best–worst method evaluates the relative importance of parent nodes, combined with a leakage-weighted summation algorithm to generate conditional probability tables. The model was applied to a western Chinese STPP and the results show the probabilities of receiver blockage, pipeline blockage, tank leakage, and heat exchanger blockage are 0.061, 0.059, 0.04, and 0.08, respectively. Under normal operating conditions, the occurrence rates of level II accident consequences for all four equipment types remain below 6%, with response measures demonstrating significant suppression effects on accidents. The research results provide critical decision-making support for risk management and mitigation strategies in STPPs. Full article

Road traffic injuries (RTIs) and air pollution present dual burdens that disproportionately affect school-going children in low-income urban settings like Malawi. Despite availability of evidence-based interventions, their implementation often overlooks local contexts and perspectives. This study aimed to elicit stakeholder input on interventions addressing RTIs and air pollution exposure among children in urban Blantyre through stakeholder engagement. It used a mixed method Delphi technique combining expert consultations with community focus groups to achieve consensus on interventions. Successive rounds of prioritization and qualitative discussions explored contextual barriers and facilitators to implementation. Stakeholders identified 40 interventions, 23 for road safety and 17 for air pollution. Measures prioritized by experts included speed limit enforcement, pedestrian infrastructure improvements, and emission controls. Contextual barriers identified by experts and the community included socio-political and financial constraints. Community perspectives emphasized behavioral interventions, while experts highlighted systemic and legislative changes. The study underscored the value of combining expert and community perspectives to design context-sensitive interventions. Synergies between road safety and air pollution interventions offer opportunities for dual benefits but require careful adaptation to urban Malawi’s realities. This study provides a model for participatory design in low-income settings, emphasizing stakeholder engagement for tailored solutions. Full article

Diffuse agricultural pollution is a leading contributor to surface water degradation, particularly in regions undergoing rapid land use change and agricultural intensification. In many developing countries, conventional assessment approaches fall short of capturing the spatial complexity and cumulative nature of multiple environmental drivers that influence surface water vulnerability. This study addresses this gap by introducing the Integral Index of Vulnerability to Diffuse Contamination (IIVDC), a spatially explicit, multi-criteria framework that combines the Analytical Hierarchy Process (AHP) with Geographic Information Systems (GIS). The IIVDC integrates six key indicators—slope, soil erodibility, land use, runoff potential, hydrological connectivity, and observed water quality—weighted through expert elicitation and mapped at high spatial resolution. The methodology was applied to the Guachal River watershed in Valle del Cauca, Colombia, where agricultural pressures are pronounced. Results indicate that 33.0% of the watershed exhibits high vulnerability and 4.3% very high vulnerability, with critical zones aligned with steep slopes, limited vegetation cover, and strong hydrological connectivity to cultivated areas. By accounting for both biophysical attributes and pollutant transport pathways, the IIVDC offers a replicable tool for prioritizing land management interventions. Beyond its technical application, the IIVDC contributes to sustainability by enabling evidence-based decision-making for water resource protection and land use planning. It supports integrated, spatially targeted actions that can reduce long-term contamination risks, guide sustainable agricultural practices, and improve institutional capacity for watershed governance. The approach is particularly suited for contexts where data are limited but spatial planning is essential. Future refinement should consider dynamic water quality monitoring and validation across contrasting hydro-climatic regions to enhance transferability. Full article

Background: Establishing safe and efficient oral feeds for preterm infants is one of the last milestones to be achieved prior to discharge home. However, this process commonly elicits stress and anxiety in both care providers, such as nurses and the entire healthcare team in the Neonatal Intensive Care Unit (NICU), as well as parents. These feelings of uncertainty are exacerbated by the non-linear progression of oral feeding development and the absence of a systematized approach to initiate and advance feedings. Methods: In this 48-bed tertiary perinatal centre, staff surveys and a needs assessment showed dissatisfaction and increasing stress and anxiety due to the inconsistencies in initiating and advancing oral feeds. This paper describes the formation of a multidisciplinary feeding committee which reviewed various oral feeding training materials and the ultimate creation of two innovative oral feeding algorithms and their corresponding education materials. Results: The Sunnybrook Feeding Committee has developed two evidence-based algorithms, one for initiating oral feeds and another for monitoring progress with objective decision-making points during common oral feeding challenges. To complement and support these algorithms, educational materials and a comprehensive documentation process were also created. These resources included detailed instructions, visual aids, and step-by-step guides to help staff understand and apply the algorithms effectively. Additionally, the educational materials aimed to standardize training and ensure consistency across the NICU, further promoting a systematic approach to preterm oral feeding. Implementation of these algorithms also aimed to provide evidence-based, expert-guided guidelines for assessing readiness, initiating feeds, monitoring progress, and making necessary adjustments. Conclusions: This structured approach lays the foundation for a unit-wide language and systematic process for oral feeding. The next steps in this quality improvement project involve educating and piloting the implementation of the developed oral feeding algorithms, gathering staff feedback, and refining the tools accordingly. The goal is to enhance overall care quality, reduce stress for both care providers and parents, and ensure the best possible start for vulnerable preterm infants, ultimately supporting a smooth and successful transition to home. Full article

The valuation of the benefits to humans of ecosystem services (ESs) provided by nature has become increasingly important. A current challenge is the measurement of the range of benefits which are not traded in the marketplace and are generally considered intangible, with further challenges to even classify them formally, e.g., as cultural ecosystem services (CESs). Previous studies have emphasized a related challenge: the strong need for engagement of not just experts but ’ordinary people’. Approaches using participatory approaches and less formal communication pathways to draw out local CES values have been reported. However, critical reflections of those studies reported significant differences in understanding between ’outsider researchers’ and ’locals’, calling validity deeply into question. Even deliberative approaches backfired by significantly modifying local social constructs during elicitation. In this study, we demonstrate a fundamentally different kind of approach, developed from the bottom–up sustainability indicator development process called WeValue InSitu. It focuses not on improving deeper top–down ‘engagement’ of a specific topic, but instead on improving local articulation of existing envelopes of in situ human shared values, naturally integrated. The WeValue InSitu output is a framework of separate but interlinked concise Statements of local shared values. Some of these Statements may refer to values concerning ecosystems, but situated amongst others. Here, we analyze the outputs from 23 convenience groups in three sites in Nigeria and investigate the shared values found empirically against existing economics-based MEA classifications. The findings include hybrid values which span existing CES sub-categories and even across into market-based categories. This opens a discussion as to whether future ES valuation frameworks might evolve more usefully with foundations built on empirically derived typologies of human values, rather than bolt-on modifications to financially based economics concepts. It also raises questions about the validity of current valuations made which cannot capture empirically found human values. Full article

The cosmetics industry requires a long-term, sustainable vision to reduce its impact on the environment. Within this process, packaging is of critical relevance, as it impacts the ecological footprint of products and determines consumers’ perception of the product as sustainable and green while shaping their willingness to purchase the product. This article implements a mixed-methods design to combine theoretical insights with the opinions of experts and the perceptions of consumers. It elicits which packaging elements are the most important in determining consumers’ willingness to pay for green cosmetics and which are the most important regarding their perception of the product being sustainable and green. The results of the conjoint analysis-based study conducted in Germany indicate the predominance of the used materials for packaging over other characteristics (glass +EUR 1, bio-based materials +EUR 0.92, recycled plastic +EUR 0.75 vs. wood as base category). Labels (Veganblume +EUR 0.68, Cruelty-Free +EUR 0.11) and the availability of refill options (+EUR 0.61) score in second place, while coloring (black −EUR 0.2, green −EUR 0.11, brown −EUR 0.13 vs. white as the base category) and QR codes (+EUR 0.13) score last regarding participants’ willingness to purchase the product. The results also reveal a distinct difference between the order of attributes driving the willingness to pay and those driving the perception of the sustainability of a product. Regarding sustainability perception, the relevance of labels and color increases distinctly, while package material remains the dominant attribute. Full article

Indigenous women experience disproportionately higher rates of adverse health outcomes. Few studies have explored the root of these problems or defined health and wellness from the perspectives of Indigenous women. Our objective was to elicit views on Indigenous women’s health from women who are Indigenous and/or have experience working with Indigenous communities across Turtle Island and Hawai‘i (e.g., United States). Informed by intersectionality as a social critical theory, we convened a workshop to engage in a co-creative consensus-building and expert decision process using design thinking. The two-day workshop embraced Indigenous values of land, sacred spaces, genealogy, family, rituals, and culture. Participants included United States-based Native and Indigenous women (n = 16) and allies (n = 7). Participants focused on answering key questions such as “What are priority areas for Indigenous women’s health”? and “What are the key facilitators and barriers to improving Indigenous women’s health”? Co-created priority lists for each of these topics were generated. Participants overwhelmingly reported satisfaction with the workshop process and emphasis on a strength-based, culturally driven approach to share their stories, which contextualized the ideas, concerns, and priorities of Indigenous women who self-reflected on their own health and wellness. Creating culturally safe spaces for Indigenous people to reflect on their own hopes for the future relates to the theme by describing a process to bridge traditional healing with modern-day practices to build pilina. Full article

Comprehending intermarket relationships among asset classes/commodities and the changing dynamics among the gold, bitcoin, and oil markets under high or low-volatility indexes is now imperative for investors. This paper presents a qualitative study to elicit expert views on the relationships between two major commodities (gold and oil) and bitcoin, specifically emphasizing the pre- and post-COVID-19 era. The thematic analysis of 30 finance experts revealed gold as a safe haven and portfolio diversifier; however, it has lost importance as an inflation hedge post-COVID-19 (2020–2022). Moreover, findings indicated that bitcoin was not a substitute for gold and that there was a positive correlation between gold and oil and the gold volatility index (VIX). Furthermore, there was a negative correlation between the oil VIX and the bitcoin VIX, with no correlation between the gold–bitcoin or oil–bitcoin nexus. These findings are pertinent for investors and scholars in the context of portfolio allocation/portfolio design that comprise these vital asset classes/commodities. Full article

Background and Objectives: Diabetes is a rapidly increasing global health challenge compounded by a critical shortage of diabetes care and education specialists. Robot-assisted diabetes care offers a cost-effective and scalable alternative to traditional methods such as training and dispatching human experts. This pilot study aimed to evaluate the feasibility of using robots for diabetes care consultations by examining their ability to elicit meaningful patient feedback, identify therapeutic issues, and assess their potential as substitutes for human specialists. Materials and Methods: A robot-assisted consultation programme was developed by selecting an appropriate robot, designing the programme content, and tailoring back-channel communication elements. Experienced diabetes care nurses operated the robot during the consultations. Patient feedback was collected through a 17-item questionnaire using a five-point Likert scale (evaluating functionality, impressions, and effects). Additionally, a five-item questionnaire was used to assess whether the programme helped patients reflect on the key therapeutic domains of diabetes knowledge, diet, exercise, medications, and blood glucose control. Results: This study included 32 participants (22 males; mean age, 69.7 ± 12.6 years; mean HbA1c, 7.2 ± 1.0%). None of the participants reported any discomfort during the consultation. Sixteen of the seventeen feedback items scored above the median of 3, as did all five therapeutic reflection items. The interview content analysis revealed the programme’s ability to differentiate patients facing issues in treatment compliance from those effectively managing their condition. Robots can elicit valuable patient narratives like human specialists. Conclusions: The results of this pilot study support the feasibility of robot-assisted diabetes care to assist human experts. Future research should explore the programme’s application with healthcare professionals with limited experience in diabetes care, further demonstrating its scalability and utility in diverse healthcare settings. Full article