Search Results (82)

The operational roles of artificial intelligence in energy security remain inconsistently defined across the scientific literature. To address this gap, the present review examines 165 peer-reviewed abstracts published between 2021 and 2025 using a triangulated methodology that combines trigram frequency analysis, manual qualitative coding, and semantic clustering with sentence embeddings. Eight core roles were identified: forecasting and prediction, optimisation of energy systems, renewable energy integration, monitoring and anomaly detection, grid management and stability, energy market operations/trading, cybersecurity, and infrastructure and resource planning. According to the results, the most frequently identified roles, based on the average distribution across all three methods, are forecasting and prediction, optimisation of energy systems, and energy market operations/trading. Roles such as cybersecurity and infrastructure and resource planning appear less frequently and are primarily detected through manual interpretation and semantic clustering. Trigram analysis alone failed to capture these functions due to terminological ambiguity or diffuse expression. However, correlation coefficients indicate high concordance between manual and semantic methods (Spearman’s ρ = 0.91), confirming the robustness of the classification. A structured typology of AI roles supports the development of more coherent analytical frameworks in energy research. Future research incorporating full texts, policy taxonomies, and real-world use cases may help integrate AI more effectively into energy security planning and decision support environments. Full article

The increasing frequency and sophistication of cyber attacks have posed significant challenges for digital financial organisations, particularly in quantifying their multidimensional impacts. These challenges are largely attributed to the lack of a standardised cyber impact taxonomy, limited data availability, and the evolving nature of technological threats. As a result, organisations often struggle with ineffective security investment prioritisation, reactive incident response planning, and the inability to implement robust, risk-based controls. Hence, an efficient and comprehensive approach is needed to quantify the diverse impacts of cyber attacks in digital financial services. This paper presents a systematic review and examination of the state of the art in cyber impact quantification, with a particular focus on digital financial organisations. Based on a structured search strategy, 44 articles (out of 637) were selected for in-depth analysis. The review investigates the terminologies used to describe cyber impacts, categorises current quantification techniques (pre-attack and post-attack), and identifies the most commonly utilised internal and external data sources. Furthermore, it explores the application of Machine Learning (ML) and Deep Learning (DL) techniques in cyber security risk quantification. Our findings reveal a significant lack of standardised taxonomy for describing and quantifying the multidimensional impact of cyberattacks across physical, digital, economic, psychological, reputational, and societal dimensions. Lastly, open issues and future research directions are discussed. This work provides insights for researchers and professionals by consolidating and identifying quantification technique gaps in cyber security risk quantification. Full article

This paper proposes a KeyBERT-based method for constructing a knowledge graph of the electronic information curriculum system, aiming to enhance the structured representation and relational analysis of educational content. Electronic Information Engineering curricula encompass diverse and rapidly evolving topics; however, existing knowledge graphs often overlook multi-word concepts and more nuanced semantic relationships. To address this gap, this paper presents a KeyBERT-enhanced method for constructing a knowledge graph of the electronic information curriculum system. Utilizing teaching plans, syllabi, and approximately 500,000 words of course materials from 17 courses, we first extracted 500 knowledge points via the Term Frequency–Inverse Document Frequency (TF-IDF) algorithm to build a baseline course–knowledge matrix and visualize the preliminary graph using Graph Convolutional Networks (GCN) and Neo4j. We then applied KeyBERT to extract about 1000 knowledge points—approximately 65% of extracted terms were multi-word phrases—and augment the graph with co-occurrence and semantic-similarity edges. Comparative experiments demonstrate a ~20% increase in non-zero matrix coverage and a ~40% boost in edge count (from 5100 to 7100), significantly enhancing graph connectivity. Moreover, we performed sensitivity analysis on extraction thresholds (co-occurrence ≥ 5, similarity ≥ 0.7), revealing that (5, 0.7) maximizes the F1-score at 0.83. Hyperparameter ablation over n-gram ranges [(1,1),(1,2),(1,3)] and top_n [5, 10, 15] identifies (1,3) + top_n = 10 as optimal (Precision = 0.86, Recall = 0.81, F1 = 0.83). Finally, GCN downstream tests show that, despite higher sparsity (KeyBERT 64% vs. TF-IDF 40%), KeyBERT features achieve Accuracy = 0.78 and F1 = 0.75, outperforming TF-IDF’s 0.66/0.69. This approach offers a novel, rigorously evaluated solution for optimizing the electronic information curriculum system and can be extended through terminology standardization or larger data integration. Full article

Extensive research in the field of construction safety has predominantly focused on identifying the causes and impacts of construction accidents, evaluating safety plans, assessing the effectiveness of safety education materials, and analyzing relevant policies. However, comparatively limited attention has been given to the systematic formation, management, and utilization of safety-related information and knowledge. Despite significant advancements in information and knowledge management technologies across the architecture, engineering, and construction (AEC) industries, their application in construction safety remains underdeveloped. This study addresses this gap by proposing a novel ontology-based framework specifically designed for construction safety management. Unlike previous models, the proposed ontology integrates diverse safety regulations and terminologies into a unified and semantically structured knowledge model. It comprises three primary superclasses covering key areas of construction safety, with an initial focus on fall hazards—one of the most frequent and severe risks, particularly in roofing activities. This domain-specific approach not only improves semantic clarity and standardization but also enhances reusability and extensibility for other risk domains. The ontology was developed using established methodologies and validated through reasoning tools and competency questions. By providing a formally structured, logic-driven knowledge base, the model supports automated safety reasoning, facilitates communication among stakeholders, and lays the foundation for future intelligent safety management systems in construction. This research contributes a validated, extensible, and regulation-aligned ontology model that addresses critical challenges in safety information integration, sharing, and application. Full article

Objectives: The term ‘prosthesis’ in reference to breast implants is used to clarify its distinction from the general term ‘breast implant’, which is widely adopted by plastic surgeons. This terminology highlights the role of the implant as a functional tissue substitute, particularly in post-mastectomy reconstruction, rather than solely as a cosmetic enhancement. This distinction is relevant for understanding the long-term implications of implant-based reconstruction and the associated complications. The aim of this systematic review was to compile and analyze the current evidence on the long-term complications associated with breast implants. We explored how these complications vary depending on implant type, surgical techniques, patient-specific factors, and the indication for implantation (cosmetic vs. reconstructive). These indications were analyzed separately to avoid assumptions regarding their correlation with surgical techniques. Methods: A systematic search was conducted across PubMed, Web of Science, and Scopus for studies published up to December 2024, following PRISMA 2020 guidelines and the Cochrane Handbook for Systematic Reviews of Interventions. An initial search identified 1480 studies. After screening and applying inclusion criteria, 11 studies were selected for the final analysis. Studies included in this review reported long-term complications in human subjects, were published in English, and evaluated breast implants. The quality of the included studies was assessed using the ROBINS-E tool. Additionally, subgroup analyses examined differences based on implant type (silicone vs. saline), surgical techniques, and patient characteristics, such as age, comorbidities, and the duration of follow-up. Results: This review study was performed between September 2024 and December 2024. A total of 11 studies were included in the review. The included studies were published between 1997 and 2021, providing a long-term perspective on breast implant complications. The most frequently reported complications were capsular contracture, implant rupture, seroma, and infection, with capsular contracture being the most prevalent. Silicone implants were associated with a higher risk of rupture compared to saline implants. Techniques using textured implants and dual-plane placements were found to reduce the incidence of capsular contracture. Patient-related factors, such as age and smoking status, were identified as significant risk factors for complications, while longer follow-up periods revealed more late-onset complications. Conclusions: This review underscores the importance of understanding the long-term risks of breast implants and highlights the need for personalized surgical planning and thorough follow-up care. Future studies should focus on standardizing outcomes reporting and further evaluating the safety and effectiveness of new implant materials and surgical approaches. Full article

Although HBIM (Historical Building Information Modeling) excels in geometric data acquisition and modeling within Scan-to-BIM (Building Information Modeling) workflows, its application in digital documentation faces persistent challenges, such as balancing precision and efficiency, ambiguous information structures, and the absence of standardized protocols. To address these issues, this study refines key steps from the systematic Scan-to-BIM process and proposes a documentation-oriented HBIM workflow. The workflow is designed to tackle data complexity and semantic alignment challenges through detailed strategic planning, standard data collection, efficient geometric modeling, and ontology-based information integration. Validated in the Valentino Castle’s north wing digital archiving project, the proposed framework emphasizes archival management and standardization, reducing reliance on high-precision point cloud data and complex geometric modeling. Instead, it adopts low-precision geometric models as information storage containers, employing standardized information structures to manage and transfer heterogeneous data. Key contributions include the following: (1) establishing a requirements-driven and model-level-based framework for standardized project management; (2) introducing a component alignment concept to harmonize IFC (Industry Foundation Classes) standards and traditional terminologies; and (3) developing a four-level information structure to enhance HBIM parameter and database management. The workflow significantly reduces data acquisition and modeling time while offering a replicable methodology for heritage documentation, promoting cross-disciplinary collaboration and standardization in digital preservation practices. Full article

The adoption of remanufacturing technology is gaining traction, considering sustainability principles and the goal of fostering a resource-efficient society. However, given the unique environment of construction sites and the context of incorporating lean production into remanufacturing, implementing remanufacturing concepts in the construction industry presents significant obstacles. The goal of this article is to provide guidance and recommendations for construction professionals when developing remanufacturing plans, including circumstances, insights, and methodology for implementation. Initially, this study distinguishes the widely used ‘3R’ terminology (reduce, reuse, and recycle) from the concept of remanufacturing applicable to the construction industry. It then investigates the characteristics of the ‘core’ (items to be remanufactured) of construction components, as well as evaluates and restructures key influencing aspects associated with remanufacturing techniques. A careful assessment of the literature and detailed descriptions help to clarify these factors. The findings show that these criteria have a double impact on remanufacturing and that successful remanufacturing techniques necessitate a mix of flexibility, safety, and stability. Finally, a ‘tumbler’ approach was offered for experts in construction component professionals, allowing key influencing factors to play a more inclusive and dependable role in the development of remanufacturing strategies. Full article

Urban development is increasingly scrutinized for its sustainability from an economic, social, and environmental viewpoint. This study emphasizes how important indicators are in capturing the complexity of urban settings when assessing urban landscapes and making sure that comprehensive development plans incorporate all these aspects. The work aim is to forward the investigation of the ontology of indicators related to urban sustainability, specifically, a framework for spatial and temporal analysis and an attempt to align terminology with the sustainability indicators of the ISO spectrum. The methodology encompasses three main phases: a systematic review of sustainability indicators from the scientific literature across various territorial scales; the mapping of individual indicators to their appropriate spatial–temporal measurement ranges; and the alignment of these spatially and temporally specific indicators with ISO standards. Focusing on the Italian context, this study establishes an ontological spatial–temporal framework. It analyzes ISO indicators that can be managed in Italian spatial settings. The main objective of this part of the research is to select through a critical analysis the most frequent indicators in order to be able to make an alignment and define those that aim more at the goals of the 2030 Agenda on sustainability. This innovative approach enhances urban issue awareness and supports informed decision-making by demonstrating how sustainability indicators can be effectively utilized in downscaling strategies to create a policy for the practical use of indicators. Full article

This study examines the sector-specific linguistic strategies utilized by large Italian firms, emphasizing the relationship between language, corporate governance procedures, and sustainability initiatives. This research employs a content analysis of 210 sustainability reports (SRs) from 203 corporations, categorizing firms into seven industry-specific clusters and examining how various sectors communicate sustainability activities. The research utilizes language game theory to determine if the vocabulary employed in SRs promotes a uniform comprehension of sustainability activities and aids stakeholders in assessing company sustainability plans. Key findings indicate a substantial disparity in the terminology employed across various businesses, underscoring the fragmentation and sector-specific focus in SR procedures. The research reveals sector-specific linguistic techniques that influence the discourse on sustainability, illustrating how language is deliberately employed to correspond with each sector’s objectives and governance frameworks. This research enhances academic literature by incorporating language game theory into SR analysis, revealing the influence of sector-specific language on sustainability narratives. It also underscores the issues associated with positive framing and the potential for greenwashing, wherein optimistic rhetoric may compromise the integrity and trustworthiness of SRs. The results necessitate standardized reporting systems to improve the comparability and accountability of systematic reviews across various sectors. Full article

Background: Nutritional status is an important factor influencing toxicity of treatment. Nutritional assessment indicators such as the Prognostic Nutritional Index (PNI), Controlling Nutritional Status (CONUT) score and modified Glasgow Prognostic Score (mGPS) have been reported to be associated with treatment-related adverse events (AEs) for various malignancies. However, there are no reports investigating the relationship between nutritional status and AEs from poly-(ADP-ribose) polymerase (PARP) inhibitors (PARPi), which are widely used in recent years as maintenance therapy for ovarian cancer. Objective: The primary objective was to investigate the usefulness of nutritional assessment indicators in predicting treatment discontinuation due to AEs from PARPi. Methods: This multicenter retrospective study included patients diagnosed with ovarian cancer who received maintenance therapy with PARPi from January 2018 to December 2023. PNI, CONUT score, and mGPS were calculated based on hematological parameters measured within 7 days before the start of PARPi therapy. Results: A total of 272 patients received maintenance therapy with PARPi during the period, but due to the absence of the blood collection of albumin levels within one week or other exclusion criteria, 71 patients were finally included in this analysis. AEs were seen in 59 patients (83.1%), including 25 (35.2%) severe events (grade ≥3 in Common Terminology Criteria for Adverse Events v5.0). Eighteen patients (25.4%) discontinued treatment due to PARPi-related AEs. Low PNI (<48.44) and high mGPS (≥1) were predictors of treatment discontinuation in both univariate and multivariate analyses. CONUT was not a significant predictor in this study. Conclusions: Our study suggested that PNI and mGPS can predict the risk of treatment discontinuation due to PARPi-related AEs before starting maintenance therapy. This insight opens avenues for more personalized treatment plans, potentially improving patient outcomes. Full article

Clinicians have a sincere desire to ensure that the decision-making processes of seriously ill patients are well informed throughout illness trajectories. A quagmire of variable terminology (e.g., advance care planning, serious illness conversations, goals-of-care discussions, etc.), however, currently predominates the field of serious illness communication. This creates uncertainty among clinicians as to the overall purpose, tasks, and specific outcomes of conversations that address serious illness. The Preparing or Deciding model is a unifying framework that provides conceptual clarity by helping clinicians understand their role in leading these important conversations. The Preparing or Deciding model simply posits that conversations with seriously ill patients are about either preparing or deciding. It considers these tasks to be mutually exclusive, which can help bypass many of the barriers to having these conversations. The Preparing or Deciding model compliments all existing resources and frameworks and is applicable to all healthcare practitioners in every care setting. To help move forward serious illness communication education and research, as well as process improvement efforts more effectively, here, we describe the Preparing or Deciding model. Full article

Purpose: Ocular trauma is a major cause of visual impairment; however, little is known about its burden in Saudi Arabia. Therefore, this study aimed to determine the epidemiological characteristics of ocular trauma in pediatric patients in Riyadh, Saudi Arabia. Patients and methods: Medical records of pediatric patients diagnosed with eye injuries between January 2016 and December 2020 were retrospectively reviewed. Demographic and injury characteristics were collected, and ocular trauma injuries were classified according to the Birmingham Eye Trauma Terminology. Results: A total of 855 injured patients were included in the study, of whom 525 (61.4%) were boys. Patient age ranged from one month to 18 years. Most ocular injuries occurred in children aged 5–9 years. The injuries were more prevalent in boys than in girls. Closed globe injuries accounted for 70% of cases, open globe injuries for 21%, and other injuries for 9%. Most ocular injuries occurred at home (n = 87, 42%), followed by school (n = 61, 30%). Conclusions: These results may inform the implementation and targeting of interventions to reduce or prevent eye injuries in children. Further, they highlight the importance of well-planned prevention programs to prevent eye injuries from occurring in children’s daily lives. Full article

Aims: This review aims to analyze the multiple factors affecting the staging of the orthodontic tooth movement during clear aligner treatment and to provide an efficient work methodology in this regard during digital treatment planning. Materials and Methods: A literature search was conducted on electronic databases (Pubmed, Scopus, Google Scholar and CNKI). The results of the present study have been divided into several sections: (1) definition and concept of staging, (2) basic principles of clear aligners, (3) macro-staging, (4) micro-staging, and (5) limitations. Results: The terminology of macro-staging and micro-staging proposed in this paper aims to be a first step towards a more detailed analysis of staging. The macro-staging constitutes the general biomechanics of movements that need to be prioritized to meet the objectives of the treatment plan. It provides a comprehensive view of the movements occurring in each dental arch. The micro-staging constitutes the biomechanics of movements for each individual tooth. This involves studying the movements in the different planes of space in which each tooth is programmed, deciding if they are compatible, and having strategies to create space to avoid lack of expression. Conclusions: Further studies should focus on exploring different staging approaches to address similar malocclusions to determine which are the most effective and applicable to clinical practice. Full article

Non-alcoholic fatty liver disease (NAFLD) is a common long-lasting liver disease that affects millions of people around the world. It is best identified with a hepatic fat build-up that ultimately leads to inflammation and damage. The classification and nomenclature of NAFLD have long been a controversial topic, until 2020 when a group of international experts recommended substituting NAFLD with MAFLD (metabolic dysfunction-associated FLD). MAFLD was then terminologically complemented in 2023 by altering it to MASLD, i.e., metabolic dysfunction-associated steatotic liver disease (MASLD). Both the MAFLD and the MASLD terminologies comprise the metabolic element of the disorder, as they offer diagnostic benchmarks that are embedded in the metabolic risk factors that underlie the disease. MASLD (as a multisystemic disease) provides a comprehensive definition that includes a larger population of patients who are at risk of liver morbidity and mortality, as well as adverse cardiovascular and diabetes outcomes. MASLD highlights metabolic risks in lean or normal weight individuals, a factor that has not been accentuated or discussed in previous guidelines. Novel antihyperglycemic agents, anti-hyperlipidemic drugs, lifestyle modifications, nutritional interventions, and exercise therapies have not been extensively studied in MAFLD and MASLD. Nutrition plays a vital role in managing both conditions, where centralizing on a diet rich in whole vegetables, fruits, foods, healthy fats, lean proteins, and specific nutrients (e.g., omega-3 fatty acids and fibers) can improve insulin resistance and reduce inflammation. Thus, it is essential to understand the role of nutrition in managing these conditions and to work with patients to develop an individualized plan for optimal health. This review discusses prevention strategies for NAFLD/MAFLD/MASLD management, with particular attention to nutrition and lifestyle correction. Full article

Pedestrianization is a significant discourse focus within urban planning and design research. However, the need for more clarity from the inconsistent use of near-synonym concepts or terms necessitates attention. This review article addresses this issue through a comprehensive analysis of synonym proliferation in pedestrian research, culminating in developing a robust “near synonymous toolkit” and “synonym selection framework”. Employing a linear snowball sampling technique, numerical analysis, and a qualitative content analysis-based summative approach, we examined sixteen peer-reviewed articles from 11 scientific journals. Through systematic classification based on consistency and variability, the summative review identifies three primary groups of near synonyms: dominant and widely utilized conceptual or terminological near synonymy in pedestrianization in the urban planning and design literature, near synonyms directly associated with a pedestrian, pedestrianize, and those indirectly linked to another conceptual or terminological synonymy. Further analysis delves into the nature of near-synonym concepts or terms, revealing three discernible patterns: the use of distinct, precise concepts or terms with near-synonym meanings, similar concepts or terms conveying divergent meanings, and the juxtaposition of unrelated vocabulary lacking semantic resemblance. These insights illuminate semantic relationships within the studied vocabulary, underscoring the importance of addressing inconsistency for clarity, precision, and coherence in scientific discourse. By offering practical guidance through the proposed framework, this study empowers academic researchers to navigate synonym selection adeptly, thereby enhancing the caliber of scholarly writing in urban planning and design. Full article