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Sustainability has become a central concern globally, and efforts to enhance it are being made across various fields. In line with this trend, corporate sustainability reports have become more widely published. These reports provide both financial and non-financial information on a company’s sustainability. In this context, this study aims to, first, analyze the key keywords contained in CEO messages. Second, it examines whether the keywords emphasized by CEOs change in response to shifts in corporate risk under economic uncertainty. Finally, it identifies how the categories of words included in these messages are classified. To address these research questions, text analysis was selected as the methodology. Specifically, a qualitative research approach using text mining and CONCOR analysis was conducted on the text from sustainability report. According to the Term Frequency and Term Frequency-Inverse Document Frequency analyses, the most frequently occurring keywords were ESG, Sustainable, Society, Stakeholders, Growth, Environment, Effort, and Future. Centrality analysis identified the following keywords as having high centrality: Sustainable, ESG, Society, Environment, Growth, Effort, and Stakeholders. Finally, CONCOR analysis revealed four clusters: Eco-friendly Energy, ESG Management, Global Crisis, and Technological Competitiveness. This study is significant in that it analyzes the major keywords and their changes within unstructured text data using text mining and CONCOR analysis, and it suggests the possibility of future quantitative analysis of non-financial information using these keywords. Full article

Artificial intelligence (AI) is transforming countless aspects of society, including possibly even who we are as persons. AI technologies may affect our flourishing for good or for ill. In this paper, we put forward principled considerations concerning flourishing and AI that are oriented towards ensuring AI technologies are conducive to human flourishing, rather than impeding it. The considerations are intended to help guide discussions around the development of, and engagement with, AI technologies so as to orient them towards the promotion of individual and societal flourishing. Five sets of considerations around flourishing and AI are discussed concerning: (i) the output provided by large language models; (ii) the specific AI product design; (iii) our engagement with those products; (iv) the effects this is having on human knowledge; and (v) the effects this is having on the self-realization of the human person. While not exhaustive, it is argued that each of these sets of considerations must be taken seriously if these technologies are to help promote, rather than impede, flourishing. We suggest that we should ultimately frame all of our thinking on AI technologies around flourishing. Full article

The prevalence of online transactions and extensive adoption of credit card payments have contributed to the escalation of credit card cyber fraud in modern society. These trends are propelled by technological advancements, which provide fraudulent actors with more opportunities. Fraudsters exploit victims’ financial vulnerabilities by obtaining illegal access to sensitive credit card information through deceptive means, such as phishing, fraudulent phone calls, and fraudulent SMS messages. This study predicts and detects potential instances of cyber fraud in credit card transactions by employing Machine Learning (ML) techniques, including Decision Tree (DT); Random Forest (RF); Logistic Regression (LR); Support Vector Machine (SVM); K-Nearest Neighbors (KNN); XGBoost; CatBoost; and sampling techniques such as Tomek Link, Synthetic Minority oversampling technique (SMOTE), Edited Nearest Neighbor (ENN), Tomek+ENN, and SMOTE+ENN. To determine the performance of the algorithms in terms of accuracy, precision, recall, F1 score, and ROC-AUC for credit card cyber fraud detection, we conducted a comparative analysis of the extant ML techniques. Full article

The present review paper focuses on the peculiar environmental and health implications of fibrous amphibole “fluoro-edenite”, a new mineral first reported in Biancavilla (Etna Mount, Sicily, Italy). Its presence has been linked to an unusually high incidence of malignant pleural mesothelioma, as seen from national surveys during 1988–1997, marking the first case study of natural occurrence of fibrous amphibole in a volcanic context. Despite remediation efforts since the cessation of quarrying activities at the “Il Calvario” quarry, the risk of fiber exposure may extend beyond urban areas to surrounding soils and volcanic formation, not fully characterized yet. This review synthesizes relevant existing literature on mineralogical and chemical features of fluoro-edenite, while also enriching current understanding with new observations from optical microscopy, stereomicroscopy, and Scanning Electron Microscopy (SEM). Our analyses reveal the presence of fluoro-edenite amphibole not only in the altered samples but, significantly, within the massive rock samples. This finding expands its known distribution and offers initial consideration on public health implications related to massive lava rock, which crops out. This study highlights the importance of ongoing monitoring, detailed geological surveys, and further research into fiber occurrences and distribution in the volcanic systems, of which Mt. Etna represents the first case of natural occurrences, in order to fully assess their impact on public health. Full article

Scientific literacy is a key element in today’s society, shaping everyday life and fostering informed decision-making and critical thinking. However, the traditional transmission of science, among other factors, has fostered a simplistic and negative view of this field of knowledge, leading to a detachment of the population from it. In this context, teachers need to assume a transformative role. To this end, it must be recognised that didactic change cannot be limited to cognitive aspects, given the relevance of attitudes as a key component of professional knowledge and as a driver of a consolidated shift. Concern about this reality leads us to describe the structure and content of scientific knowledge related to the study of Primary Education teachers’ attitudes towards the teaching of the Nature of Science and Technology. A mixed-methodological design was employed, comprising a documentary-bibliometric study with a science-mapping approach and documentary analysis. The results showed that studies often focus on the cognitive component of attitudes, mainly on beliefs about knowledge or self-efficacy. However, studies on affective or conative components remain scarce, and none have been found that comprehensively address all three components of attitudes, despite their potential to provide a deeper understanding of their role in educational change. The need to address teachers’ attitudes holistically is highlighted to better understand the evaluative and motivational factors that guide teaching practices. Likewise, the importance of moving towards studies based on educational interventions that promote the development of science as useful for life is emphasised. Full article

Scholars and practitioners of international relations and security studies view technological capabilities in general, and digital ones in particular, as crucial to enhancing state power. Among other things, digital technologies sharpen intelligence, thus reducing the likelihood of strategic surprise by improving situational awareness and strengthening deterrence. Yet the empirical record of the early twenty-first century presents a paradox: states with highly advanced digital infrastructures remain vulnerable to unexpected strategic shocks, including intelligence failures. This article develops a conceptual framework, techno-digital vulnerability, that explains why digital superiority can paradoxically increase susceptibility to strategic surprise. Drawing on international relations theory, this article identifies four interrelated mechanisms: illusions of informational completeness; structural dependence on digital systems; hypervisibility of digitally open societies; and the systematic undervaluation of low-tech adversaries. The argument is illustrated through the case of Israel’s failure to foresee the Hamas attack of 7 October 2023. The article concludes by outlining the implications for digitally advanced democracies and for the study of strategic surprise in IR. Full article

Blue economy aims to bring prosperity to coastal communities whilst also protecting natural ocean resources for future generations. But how can this vision be put into practice, especially in communities in which dependence on natural resources is high, and food and livelihood security are key concerns? This paper examines two cases of community-led nature-based enterprise in Kenya in a search for solutions to this challenge: fisheries reform through market access and gear sustainability; mangrove forest conservation and community development using carbon credit revenues. I use a ‘diverse economies framework’ for the first time in blue economy contexts to delve into the heterogeneous relations at work and in search of insights that can be applied in multiple contexts. Analysed through key informant interviews and field observation, the cases reveal a complex assemblage of institutions, knowledges, technologies, and practices within which enterprises operate. Whilst the enterprises featured are still relatively new and developing, they suggest a direction of travel for a community-led sustainable blue economy that both supports and benefits from nature recovery. The insights gained from this diverse economies analysis lead us to appreciate a sustainable blue economy as a rediscovered and reinvigorated relationship of reciprocity between society and nature—one that nurtures place-based nature-based livelihoods and nature recovery together, and which embodies a set of values and ethics shared by government, communities, and business. Full article

This study examines the behavioral intention of Muslims in Bosnia and Herzegovina to adopt blockchain-based zakat systems. It offers novel insights from a European Islamic context. Prior studies have primarily focused on Southeast Asia and the Middle East. The research develops an SEM model on an extended Unified Theory of Acceptance and Use of Technology framework. Data were collected through a survey of Bosnian Muslims. The aim was to investigate how these factors influence the acceptance of digital zakat platforms. The findings highlight the potential of blockchain to address inefficiencies and trust issues in traditional zakat management. The study shows that performance expectancy, intrinsic religiosity, and trust are significant determinants of adopting blockchain-based zakat platforms. These results emphasize both technological and faith-based drivers of acceptance. Technology can enhance the trustworthiness and inclusivity of zakat administration for a broader group of Muslims in Bosnia and Herzegovina and similar contexts. This work contributes to broader international discussions on the intersection of technology, religion and finance. The article is laying a foundation for the future development of blockchain-based zakat platforms in Muslim societies. Full article

This study aims to explain what drives consumers to adopt e-tipping in restaurants and determine whether interface-based manipulation reduces perceived autonomy, lowers satisfaction, and weakens brand favorability. Prior research indicates that when autonomy is undermined through manipulative design, satisfaction declines. This study integrates UTAUT2 and Self-Determination Theories to examine the determinants of consumers’ e-tipping intention, satisfaction, and brand favorability in Saudi restaurants. Four UTAUT2 motivators (performance expectancy, facilitating conditions, social influence, hedonic motivation) and service quality were modeled as antecedents, cultural attitude as mediator, and inferred manipulation as moderator. An online survey of restaurant consumers in Saudi Arabia who had previously engaged in e-tipping generated 607 valid responses, providing adequate sample power for PLS-SEM testing. Results show that performance expectancy, social influence, hedonic motivation, and service quality significantly predict intention; cultural attitude mediates several effects; and manipulation weakens the intention–satisfaction relationship, negatively impacting brand favorability. This research offers a theoretical contribution by extending UTAUT2 to the e-tipping context through integrating service quality as an antecedent and positioning satisfaction and brand favorability as core outcomes. It advances theory by demonstrating how technology-driven manipulation within payment interfaces influences cultural attitudes, behavioral intentions, and post-experience evaluations in a high-context, non-tipping society. Managerial and policy implications for responsible e-tipping designs are discussed. Full article

The convergence of artificial intelligence (AI), machine learning (ML), blockchain, and big data analytics is transforming the governance, sustainability, and resilience of modern banking ecosystems. This study provides a multivariate bibliometric analysis using Principal Component Analysis (PCA) of research indexed in Scopus and Web of Science to explore how decentralized digital infrastructures and AI-driven analytical capabilities contribute to sustainable financial development, transparent governance, and climate-resilient digital societies. Findings indicate a rapid increase in interdisciplinary work integrating Distributed Ledger Technology (DLT) with large-scale data processing, federated learning, privacy-preserving computation, and intelligent automation—tools that can enhance financial inclusion, regulatory integrity, and environmental risk management. Keyword network analyses reveal blockchain’s growing role in improving data provenance, security, and trust—key governance dimensions for sustainable and resilient financial systems—while AI/ML and big data analytics dominate research on predictive intelligence, ESG-related risk modeling, customer well-being analytics, and real-time decision support for sustainable finance. Comparative analyses show distinct emphases: Web of Science highlights decentralized architectures, consensus mechanisms, and smart contracts relevant to transparent financial governance, whereas Scopus emphasizes customer-centered analytics, natural language processing, and high-throughput data environments supporting inclusive and equitable financial services. Patterns of global collaboration demonstrate strong internationalization, with Europe, China, and the United States emerging as key hubs in shaping sustainable and digitally resilient banking infrastructures. By mapping intellectual, technological, and collaborative structures, this study clarifies how decentralized intelligence—enabled by the fusion of AI/ML, blockchain, and big data—supports secure, scalable, and sustainability-driven financial ecosystems. The results identify critical research pathways for strengthening financial governance, enhancing climate and social resilience, and advancing digital transformation, which contributes to more inclusive, equitable, and sustainable societies. Full article

The Australian public and broader society have little awareness of the seminal relationship between water supply and data usage/storage. Most data centers (DCs) consume large volumes of water to operate servers that supply digital society’s instantaneous 24/7 information communication systems. DC water consumption is a global issue that lacks transparency, sustainable management, and effective governance. This article analyzes current Australian legislation, policies, and industry sustainability plans to examine whether and in what ways the absence of clear water governance requirements for DC may contribute to state and national water insecurity. It shows how academic and applied discourses conceptualize, research, and respond to DC sustainability as an energy issue. This conceptualization masks the relevance of DC water usage/security. The results show that Australian legislation, policy, planning, and management lack sufficient transparency and state governance regarding the industry’s water use and accountability. Global and national DC certifications are discussed, and policy solutions are recommended to mitigate future DC pressure on water supply and related consequences. Our conclusions advocate the necessity of improving public awareness, industry accountability, and government management strategies (policy and legislation) for sustainable water practices in Australia, as artificial intelligence increases DC quantity and size, exacerbating supply and consumption in local environments that legislate against nuclear energy alternatives. Full article

Endometriosis is a complex disease that may affect a woman’s fertility and quality of life. Owing to substantial variations in symptom severity, lesion distribution, and reproductive impact, its management presents considerable clinical challenges. The most recent internationally recognized guidelines include those issued by the European Society of Human Reproduction and Embryology (ESHRE, 2022), the German Society of Gynecology and Obstetrics (DGGG/SGGG/OEGGG S2k, 2025), the World Endometriosis Society (WES), the National Institute for Health and Care Excellence (NICE, 2024), and the American College of Obstetricians and Gynecologists (ACOG, reaffirmed 2022). To provide a comprehensive overview of these recommendations, we critically compared these guidelines, with particular emphasis on the recently updated German S2k guideline. Searches were conducted through PubMed and institutional repositories using selected key terms, and the AGREE II tool (Appraisal of Guidelines for Research and Evaluation) was employed to assess methodological quality. Key clinical domains examined included indications for conservative and radical surgery, management of endometriomas and deep infiltrating endometriosis (DIE), the role of surgery before Assisted Reproductive Technology (ART), the impact of second-look procedures, and integration of psychosocial dimensions via Patient-Reported Outcome Measures (PROMs). The results show a general trend toward interdisciplinary treatment models, cautious use of radical resection techniques, and customized, symptom-based surgical interventions. Despite ongoing disagreements, there is general agreement on collaborative decision-making, preserving fertility, and adjusting surgery time and technique between the guidelines to meet the requirements of individual patients. Full article

Background/Objectives: Uterine fibroids are the most common benign neoplasms of the female genital tract, with a prevalence of 20% to 40% among women of reproductive age. Their management in the context of Assisted Reproductive Technologies (ART) represents a major clinical challenge, characterized by controversies, contrasting approaches, and a lack of shared guidelines. Indeed, the detrimental effects of fibroid treatments are not well known and may be influenced by the size, location, and number of fibroids. The impact of hysteroscopic myomectomy in women affected by submucosal myomas (FIGO classification type: G0–G2) is well documented in the current literature; however, the impact of intramural and subserosal myoma removal (FIGO types 3–8), in particular those <4/5 cm in diameter, remains controversial. The aim of the present study is to introduce and share a pragmatic surgical approach to uterine fibroid management prior to In Vitro Fertilization (IVF), to reduce the knowledge gap regarding uterine fibroid treatment. Methods: We conducted a retrospective observationally study that included 94 cases of infertile women, who underwent myomectomy at our IVF centre at Sandro Pertini Hospital, Rome, Italy, between 2020 and 2025. These patients met the inclusion criterion of having an idiopathic/tubal factor of infertility and were aged < 40. We evaluated a group of 17 women (group A) who underwent hysteroscopic myomectomy for submucosal fibroids (FIGO types 0–2) and a group of 39 women (group B) who underwent open (laparotomic) myomectomy for intramural/subserosal fibroids (FIGO types 3–8). Group B was compared with a control group of 38 women who were similar in terms of all demographic and clinical parameters and myoma features (group C) and did not want to undergo a myomectomy procedure. All surgical procedures were executed by the same expert surgeon following our proposed model: submucosal fibroids were always removed by operative hysteroscopy, while intramural/subserosal fibroids were removed if there were three or more and if they were at least 1 ≥ 3 cm in size. All enrolled patients subsequently underwent IVF treatment at our centre, which consisted of an antagonist protocol for ovarian stimulation, and all transferred embryos were of good quality according to the recent European Society of Human Reproduction and Embryology (ESHRE) classification. Results: In group A, we observed an implantation rate of 41% and a clinical pregnancy rate of 35.2%, and these results are consistent with the current literature. In group B, we obtained statistically significant differences in the implantation (31% vs. 12.9%) and pregnancy rates (28.1% vs. 7.8%) compared to group C (p = 0.02 and p = 0.03, respectively). In addition, the live birth rate was statistically higher compared to that in group C (p < 0.01). Miscarriage and preterm delivery rates were lower in group B, although the differences were not statistically significant. No severe post-surgical complications, such as uterine rupture, were observed during subsequent pregnancies. Conclusions: Despite the limited patient sample size, the monocentric experience, and the retrospective design, we emphasize the effectiveness of our proposed surgical model in women affected by myomas. Indeed, the surgical treatment of submucosal, intramural, and subserosal lesions may improve ART and pregnancy outcomes (through a higher implantation rate, pregnancy rate, and live birth rate, as well as a lower miscarriage/preterm rate). Full article

Cross-impact analysis is frequently used in scenario-analogous studies to identify critical factors influencing ecological change, strategic planning, technology foresight, resource allocation, risk mitigation, cost optimization, and decision support. Scenarios enable different organizations to comprehend prevailing situations, prepare for probable futures, and mitigate conceivable risks. Unfortunately, cross-impact analysis methods are often criticized for their difficulty in handling complex interactions, cognitive bias, time-intensiveness, heavy reliance on a limited pool of experts, and inconsistency in assigning judgment, which can affect the expected outcomes. This paper introduces a novel method for constructing consistent scenarios that addresses these criticisms and those associated with scenario methods. The method is based on cross-impact analysis and crowdsourcing for constructing consistent scenarios. The cross-impact analysis component of the method is based on advanced impact analysis and cross-impact balance analysis to, respectively, provide a time-efficient reduction in complex interdependent factors and construct consistent scenarios from a set of reduced factors. The crowdsourcing element leverages the cumulative intelligence of a group of experts to help mitigate cognitive bias and transparently give a more inclusive analysis. The method was implemented and validated with a practical case of renewable energy adoption, a vital challenge for socioeconomic progress and climate change resilience. While the method provides a sturdy foundation for writing scenario narratives, the result confirms its robustness for constructing consistent scenarios and suggests that the future of renewable energy adoption can be enhanced through careful cogitation of best-case, base-case, and worst-case scenarios, which include varying states of perceived value, awareness, and perceived support. These findings contribute to a more nuanced understanding of how socio-cognitive and institutional factors interact to influence the pace and direction of sustainable energy transitions. Full article

As a transition from offline to online shopping is taking place in many societies, many studies have been conducted to align products with user preferences. However, the existing collaborative filtering technology has a small number of user–item interactions, resulting in data sparsity and cold start problems. This study proposes a recommendation system that combines customer preference for an item with quantitative indicators. To this end, the Amazon dataset is used to quantify an item’s attribute information through Sentence-BERT, and emotion analysis of the review data is performed. The model proposed in this study simultaneously utilizes the attribute information and review data of an item, proving that it provides higher performance than when using review text alone. Finally, we verified that our approach significantly outperforms traditional baseline models and rating predictions and effectively improves top K recommendation indicators. In addition, ablation studies found that integrating item attributes and review emotions performs better than using them individually. This means that the complementary synthesis of objective item meanings and subjective user emotions can model user preferences more accurately, enabling personalized recommendations. Full article