Search Results (292)

For well over a century, unresolved ambiguities in defining land as a finite, non-renewable resource have often facilitated rent-seeking and shaped inequitable distributions of wealth derived from nature and collective contributions. In the absence of clear conceptual and legal distinctions between land’s intrinsic worth and the incremental value conferred by human-made improvements, communities and ecosystems were frequently denied their rightful share, thereby influencing inequitable economic, social, and environmental trajectories. Though not universal, these historical patterns now reemerge in “digital land” platforms, where data, user engagement, and communal knowledge are likewise subject to private appropriation. By bridging these classical land debates with emerging forms of digital exploitation, this article offers a novel theoretical framework that reveals how unresolved land-valuation ambiguities reappear in user-generated data ecosystems. Without robust conceptual frameworks and effective regulatory oversight, such digital spheres risk replicating the exploitative logic once attached to physical land. By clarifying these parallels, this article underscores the urgent need for well-informed governance inspired by past land policy debates—particularly those focused on equity, transparency, and sustainability. Ensuring that resource management, whether rooted in soil or servers, consistently adheres to principles of fairness and shared prosperity is essential to avert new forms of unregulated extraction and to advance more inclusive, sustainable development. Full article

The development and study of Smart Grid technologies rely heavily on high-fidelity data from Phasor Measurement Units (PMUs). However, the scarcity of real-world PMU data due to privacy, security, and variability issues poses significant challenges to researchers, developers, and related industries. To address these challenges, this article introduces the bases for a digital metrology framework, focusing on a newly designed and developed synthetic PMU data generator, that is both metrologically accurate and easy to adapt to various grid configurations for data generation from point-on-wave (PoW) data. This initial phase for a Smart Grid research framework aligns with Open Science principles, ensuring that the generated data are Findable, Accessible, Interoperable, and Reusable (FAIR). By embracing these principles, the generated synthetic data not only facilitate collaboration for Smart Grid research but also ensure their easy integration into existing Smart Grid simulation environments. Additionally, the proposed digital metrology framework for Smart Grid research will provide a robust platform for simulating real-world scenarios, such as grid stability, fault detection, and optimization. Through this open science approach, future digital metrology frameworks can support the acceleration of research and development, overcoming current limitations, e.g., lack of significant amounts of real-world scenarios by PMU data. This article also presents an initial case study for situational awareness and control systems, demonstrating the potential for future Smart Grid research framework and its direct real-world impact. All research outcomes are provided to highlight future opportunities for reusability and collaborations by a novel approach for research on sensor network metrology. Full article

The American Society of Clinical Oncology (ASCO) has released the principles for the responsible use of artificial intelligence (AI) in oncology emphasizing fairness, accountability, oversight, equity, and transparency. However, the extent to which these principles are followed is unknown. The goal of this study was to assess the presence of biases and the quality of studies on AI models according to the ASCO principles and examine their potential impact through citation analysis and subsequent research applications. A review of original research articles centered on the evaluation of predictive models for cancer diagnosis published in the ASCO journal dedicated to informatics and data science in clinical oncology was conducted. Seventeen potential bias criteria were used to evaluate the sources of bias in the studies, aligned with the ASCO’s principles for responsible AI use in oncology. The CREMLS checklist was applied to assess the study quality, focusing on the reporting standards, and the performance metrics along with citation counts of the included studies were analyzed. Nine studies were included. The most common biases were environmental and life-course bias, contextual bias, provider expertise bias, and implicit bias. Among the ASCO principles, the least adhered to were transparency, oversight and privacy, and human-centered AI application. Only 22% of the studies provided access to their data. The CREMLS checklist revealed the deficiencies in methodology and evaluation reporting. Most studies reported performance metrics within moderate to high ranges. Additionally, two studies were replicated in the subsequent research. In conclusion, most studies exhibited various types of bias, reporting deficiencies, and failure to adhere to the principles for responsible AI use in oncology, limiting their applicability and reproducibility. Greater transparency, data accessibility, and compliance with international guidelines are recommended to improve the reliability of AI-based research in oncology. Full article

In the era of open data and open science, it is important that, before announcing their new results, authors consider all previous studies and ensure that they have competitive material worth publishing. To save time, it is popular to replace the exhaustive search of online databases with the utilization of generative Artificial Intelligence (AI). However, especially for problems in niche domains, generative AI results may not be precise enough and sometimes can even be misleading. A typical example is P||Cmax, an important scheduling problem studied mainly in a wider context of parallel machine scheduling. As there is an uncovered symmetry between P||Cmax and other similar optimization problems, it is not easy for generative AI tools to include all relevant results into search. Therefore, to provide the necessary background data to support researchers and generative AI learning, we critically discuss comparisons between algorithms for P||Cmax that have been presented in the literature. Thus, we summarize and categorize the “state-of-the-art” methods, benchmark test instances, and compare methodologies, all over a long time period. We aim to establish a framework for fair performance evaluation of algorithms for P||Cmax, and according to the presented systematic literature review, we uncovered that it does not exist. We believe that this framework could be of wider importance, as the identified principles apply to a plethora of combinatorial optimization problems. Full article

This article examines the teaching of civic engagement in academic settings, focusing on its role in generating new knowledge and fostering social and personal action. The article proposes regulatory remedies to ensure a fair and balanced curriculum supporting diverse worldviews and productive discourse, promoting student civic participation. The legal principle of equal protection, enshrined in the Fourteenth Amendment, serves as the foundation. The Fourteenth Amendment emphasizes equal treatment and opportunities for all, including access to a well-rounded education. By incorporating its principles into education, the article highlights the need to promote fair, civic education that empowers all students to participate actively in their communities. I recommend regulatory remedies to solidify education’s nature and foster a balanced curriculum. The proposed remedies ensure that various worldviews are embraced, promoting productive and amicable discourse among students. Creating an inclusive learning environment also allows students to engage in critical thinking and develop a deeper understanding of diverse perspectives, ultimately enhancing their civic participation. Furthermore, the article emphasizes the importance of regulatory safeguards against biased or exclusionary educational practices to ensure that all students have equal educational opportunities, regardless of their background or beliefs. By eliminating barriers and promoting a fair educational system, students can develop the necessary knowledge and skills to contribute to their communities actively. By incorporating the legal principle of equal protection with respect to perspectives represented on campus, the article advocates for legal and regulatory remedies to promote a fair and balanced curriculum that supports diverse worldviews. Full article

This study explores the potential of the Metaverse in designing trade-fair stands for the exhibition of products and services related to the textile sector, with a particular focus on upholstery fabrics. The primary aim is to enhance relations between manufacturers and customers by leveraging virtual environments. This research is part of a broader investigation into the applications of the Metaverse within the framework of Industry 5.0, emphasizing design aspects and user engagement. The applied methodology seeks to extend the functionalities of traditional physical stands while offering a viable alternative for the promotion and sale of textile products. To create the digital environment, the Metaverse platform, Spatial.io, and its Spatial Toolkit—featuring a Unity-based template which allows for the more efficient editing of scenarios in their three-dimensional aspects—were employed. Although the template is subject to certain limitations imposed by Spatial, such as restricted access to Unity’s full capabilities, these constraints were mitigated through effective programming. This enabled the incorporation of a texture selector, allowing users to combine and visualize fabric options dynamically. The authors of this article have designed a virtual stand in alignment with client specifications by applying compositional resources grounded in basic design principles of modernity and simple structural systems. This virtual stand was tested at the Habitat Fair in Valencia 2024. The results demonstrate the promising potential of these emerging technologies in advancing the capabilities of the textile sector. Full article

Increased life expectancy and reduced fertility mean more generations are living simultaneously but with fewer members. There is also a growing group of older people (aged 80 and over) who need care and support. This impacts mutual support within families and the care provided by public or private care organisations. Across OECD countries, on average, 60% of people aged 65 years and older in 2020 reported receiving support from family members, friends and people in their social network, living inside or outside their household but not care organisations. European research shows that when older persons do not have a partner (anymore), they rely on their adult children for care and support. Given that adult children frequently serve as primary providers of informal care, our study examines their perspectives and motivations to provide future care alongside the demands and expectations of their old parents. Our study adopts a multi-actor interview approach and simultaneously looks at the perspective of 40 adult children and one of their older aged parents (65 years or older). We apply the distributive justice theory to understand how children and parents assess the expectation and fairness of support. This paper contributes to the existing literature about support behaviour between parents and children, expanding insights about the fairness of support, expectations and willingness from a multi-actor approach. Through the lens of child–parent dyads, it is seen that the principles of the distributive justice theory can be perceived as not so strict, and within family relationships, one or more principles can coexist and have underlying mechanisms. This study shows the complexity and often ambivalence of family solidarity by adopting a multi-actor approach. One of the main findings is that contrasting dyads who reject the reciprocal act of support experience feelings of guilt or misunderstanding, resulting in stress and worry. A child may not follow the expected support pattern from the parent due to competing demands such as work or the prioritisation of young children, which can reduce the support given to the older parent. Besides general contrasts and similarities between child–parent support perspectives, the analysis looked into differences regarding gender and legal relationships. Our findings only found gendered care expectations. Future research should entangle this by looking into feelings of closeness, emotional connection and considering the dynamic character of filial support over time, especially between siblings. Full article

Environmental sustainability and fairness in auction systems are becoming increasingly important as systems evolve with the integration of digital technologies. This paper introduces a novel demand-supply matchmaking (DSM) framework designed to improve fairness and sustainability in auction environments, aligning with the principles of the circular economy. The framework addresses key challenges in supply chain management, such as equitable resource distribution and the reduction of environmental footprints. The framework integrates key aspects of environmental impact assessments, fairness assessments, and behavioral analytics. This enables the simulation of bidder behavior and assessment of auction scenarios. Our simulation results demonstrate that the platform can promote sustainable, fair, and informed auction practices. By comparing our approach with existing tools, we highlight the advantages of using the DSM framework to improve sustainability and fairness in digital marketplaces. This work supports the development of platforms that integrate economic efficiency with environmental responsibility and social equity. Full article

Biologists often set out to find relevant data in an ever-changing landscape of interesting databases. While leading journals publish descriptions of databases, they are usually not recent and do not frequently update the list that discards defunct or poor-quality databases. These indices usually include databases that are proactively requested to be included by their authors. The challenge for individual biologists, then, is to discover, explore, and select databases of interest from a large unorganized collection and effectively use them in their analysis without too large of an investment. The advocation of the FAIR data principle to improve searching, finding, accessing, and inter-operating among these diverse information sources in order to increase usability is proving to be a difficult proposition and consequently, a large number of data sources are not FAIR-compliant. Since linked open data do not guarantee FAIRness, biologists are now left to individually search for information in open networks. In this paper, we propose SoDa, for intelligent data foraging on the internet by biologists. SoDa helps biologists to discover resources based on analysis requirements and generate resource access plans, as well as storing cleaned data and knowledge for community use. SoDa includes a natural language-powered resource discovery tool, a tool to retrieve data from remote databases, organize and store collected data, query stored data, and seek help from the community when things do not work as anticipated. A secondary search index is also supported for community members to find archived information in a convenient way to enable its reuse. The features supported in SoDa endows biologists with data integration capabilities over arbitrary linked open databases and construct powerful computational pipelines using them, capabilities that are not supported in most contemporary biological workflow systems, such as Taverna or Galaxy. Full article

Fairness in competitive games such as the Ultimatum Game is often defined theoretically. According to some of the literature, in which fairness is determined only based on resource allocation, a proposal splitting resources evenly (i.e., 5:5) is generally assumed as fair, and minimal deviation (i.e., 4:6) is considered enough to classify the proposal as unfair. Relying on multinomial processing tree models (MPTs), we investigated where the boundaries of fairness are located in the eye of responders, and pit fairness against relative and absolute gain maximization principles. The MPT models we developed and validated allowed us to separate three individual processes driving responses in the standard and Third-Party Ultimatum Game. The results show that, from the responder’s perspective, the boundaries of fairness encompass proposals splitting resources in a perfectly even way and include uneven proposals with minimal deviance (4:6 and 6:4). Moreover, the results show that, in the context of Third-Party Ultimatum Games, the responder must not be indifferent between favoring the proposer and the receiver, demonstrating a boundary condition of the developed model. If the responder is perfectly indifferent, absolute and relative gain maximization are theoretically unidentifiable. This theoretical and practical constraint limits the scope of our theory, which does not apply in the case of a perfectly indifferent decision-maker. Full article

This paper introduces a tontine-like annuity fund designed to provide lifelong income to its participants. Initially, each member contributes a lump-sum payment into a trust fund as a joining premium. Participants then receive benefits over time, based on their survival. As members pass away, their share of payouts is redistributed among the survivors, resulting in increased payouts for those remaining. Differing from traditional tontines, which assume a uniform mortality risk, this fund accommodates participants of various ages and allows new members to join during its operation. To accommodate these features, the authors utilize age-structured models (ASMs) to determine fair premiums for new entrants and to analyze the dynamics of benefit distribution. The core objective of this paper is to develop a pension model using ASMs, recognizing its significant potential for adaptation and expansion. The primary mathematical approach employed is the Maximum Principle from optimal control theory, which helps in deriving explicit solutions for the optimal subsidy strategy. Through numerical examples and detailed illustrations, the paper demonstrates that participants who remain in the cohort longer receive greater subsidies. Additionally, the study finds that adverse shocks lead to a smaller population and thus fewer subsidies. Conversely, starting with a larger initial cohort population tends to increase the overall population, resulting in more subsidies. However, higher costs associated with subsidies lead to their reduction. Our analysis reveals the complex interplay of factors influencing the sustainability and effectiveness of the proposed annuity model. Full article

This paper explores contemporary approaches to preserving and promoting cultural heritage by integrating game elements and advanced technologies, such as Virtual Reality (VR) and Augmented Reality (AR). In an era increasingly shaped by digital innovation, preserving cultural heritage demands new strategies to sustain engagement with historical narratives and artifacts. Emerging technologies like VR and AR offer immersive, interactive experiences that appeal to modern audiences, especially younger generations accustomed to digital environments (Bekele and Champion). Gamification—the use of game design principles in non-game contexts—has gained significant traction in education and cultural heritage, providing new methods for increasing user engagement and retention (Werbach and Hunter). By incorporating gamified features, heritage can be made more accessible, fostering emotional connections and deeper understanding (Huotari and Hamari; Zichermann and Cunningham). This aligns with the shift toward interactive digital storytelling as a tool to transform static heritage presentations into dynamic, participatory experiences (Champion and Rahaman). Central to this research is the conceptualization and development of a mobile application leveraging VR and AR to enhance user engagement and education around cultural heritage. Drawing on the principles of self-determination theory (Deci and Ryan) and empirical findings on gamified learning (Landers and Landers), the application combines educational content with interactive elements, creating an immersive learning environment. By addressing both content accessibility and interactive immersion, this application bridges the gap between traditional heritage preservation and the expectations of a digitally native audience. The recent literature underscores the potential of VR and AR in cultural preservation, emphasizing their ability to transcend physical boundaries, simulate historical environments, and promote active participation (Milgram and Kishino, Addison; Azuma). As virtual environments evolve, platforms like the metaverse expand possibilities for experiencing cultural heritage in spaces free of geographical limitations (Cipresso et al.; Radianti et al.). Such advancements have already demonstrated significant educational and experiential benefits (Wu et al.; Akçayır and Akçayır). This study employs both quantitative and qualitative methods to examine the target group’s attitudes toward gamified technologies for cultural heritage preservation. The initial results indicate substantial interest and willingness among users to engage with applications employing VR and AR. This aligns with findings in the literature that suggest immersive experiences can enhance learning outcomes and foster long-term engagement (Merchant et al.; Speicher et al.). The project has garnered significant recognition, receiving the Rector’s Award for the best scientific paper in the technical field at the University of Zagreb and earning bronze medals at the ARCA Innovation Fair and the INOVA Fair. These accolades underscore the project’s innovative approach and its potential for real-world application. By presenting a robust framework for integrating gamification and immersive technologies into cultural heritage preservation, this paper contributes to the growing discourse on utilizing advanced digital tools to ensure the sustainability and relevance of cultural heritage for future generations. Full article

The classified water pricing system is an effective measure for promoting the rational utilization of water resources under market mechanisms. Studying the water prices of three different types of water sources, including reservoir water, river water, and wastewater treatment plant effluent, is the basis for promoting the use of reclaimed water. However, there remains a spectrum of viewpoints on how to establish a pricing mechanism for reclaimed water at present. This study primarily focuses on the multi-level quality-separated water supply system in Yiwu City, China. It analyzes the limitations of the current water pricing formation mechanism and the externality of integrating reclaimed water into the unified allocation of multiple water sources. Based on the principles of full-cost water pricing and externality theory, a supply-side classified water pricing permit cost and pricing calculation model, covering the entire process of the social water cycle, is proposed. It focuses on the analysis of the impact of equity costs and environmental costs on supply-side classified water pricing. The Shapley value method is used for the technology of cost allocation among stakeholders to reasonably distribute the calculated water pricing of reclaimed water. The price of reclaimed water varies depending on the user type, with residential users paying 2.93 CNY/t, industrial users 4.00 CNY/t, and government allocations at 8.52 CNY/t. Compared with the classified water prices of various stakeholders on the user side of reservoir water, reclaimed water has a significant price advantage. This research demonstrates that the supply-side classified water pricing model, which includes a permit cost and pricing calculation framework, can encourage the supply of higher-quality water at corresponding higher prices, while also providing the internalization of external costs. Furthermore, the Shapley value method of cost allocation can realize the fair burden of stakeholders on the calculated water price and maintain the competitive advantage of reclaimed water prices. Full article

This study conducts an ethics-centered analysis of the AI/ML models used in Student Mental Health (SMH) research, considering the ethical principles of fairness, privacy, transparency, and interpretability. First, this paper surveys the AI/ML methods used in the extant SMH literature published between 2015 and 2024, as well as the main health outcomes, to inform future work in the SMH field. Then, it leverages advanced topic modeling techniques to depict the prevailing themes in the corpus. Finally, this study proposes novel measurable privacy, transparency (reporting and replicability), interpretability, and fairness metrics scores as a multi-dimensional integrative framework to evaluate the extent of ethics awareness and consideration in AI/ML-enabled SMH research. Findings show that (i) 65% of the surveyed papers disregard the privacy principle; (ii) 59% of the studies use black-box models resulting in low interpretability scores; and (iii) barely 18% of the papers provide demographic information about participants, indicating a limited consideration of the fairness principle. Nonetheless, the transparency principle is implemented at a satisfactory level with mean reporting and replicability scores of 80%. Overall, our results suggest a significant lack of awareness and consideration for the ethical principles of privacy, fairness, and interpretability in AI/ML-enabled SMH research. As AI/ML continues to expand in SMH, incorporating ethical considerations at every stage—from design to dissemination—is essential for producing ethically responsible and reliable research. Full article

Background: Person-centredness, a global movement in healthcare, is consistent with international developments in healthcare policy. It is important to have instruments to measure person-centred care. The Person-Centred Practice Inventory-Staff (PCPI-S) is an internationally recognized instrument that aims to measure how healthcare staff experience person-centred practice. Aim: To perform the cultural adaptation and psychometric testing of a Spanish version of the PCPI-S (PCPI-S (Sp)). Method: A two-stage research design was implemented as follows: (1) the translation and cultural adaptation of the PCPI-S from English to Spanish using the “Translation and Cultural Adaptation of Patient Reported Outcomes Measures-Principles of Good Practice”; (2) a quantitative cross-sectional survey for the psychometric evaluation of the PCPI-S. Test–retest reliability was evaluated using the Kendall tau concordance coefficient, internal reliability was assessed through the ordinal theta (OT) coefficient, and confirmatory factor analysis was performed to examine the theoretical measurement model. Results: A Spanish version of the PCPI-S was obtained. There were no significant difficulties in the translation process or the consulting sessions. A sample of 287 healthcare professionals participated in the study at least once. All the items showed at least a fair level of test–retest reliability. The OT scores were adequate (>0.69). The model showed good to adequate levels of fit: CFI = 0.89, SRMR = 0.068; RMSEA = 0.060 with CI90% (0.056–0.063). Conclusions: The Spanish translation of the PCPI-S was psychometrically valid when tested with Spanish healthcare professionals. This instrument will help identify professionals’ perceptions of person-centred practice, track the evolution of this practice over time, and assess interventions aimed at improving person-centred practice. Full article