Adolfo Muñoz

Rumors, misleading claims, and other factually risky information units may gain visibility during crises before verification processes are complete. Existing detection systems often address factual status or diffusion separately, whereas operational monitoring requires identifying units that are both factually risky and highly amplified by a forecast horizon. This paper proposes the Disinformation Diffusion Virality Risk Index (DDVRI), an explainable early-warning framework for estimating this joint risk from evidence observed during a prespecified early window. The formulation defines early histories, adjudicated factual labels, fold-specific amplification thresholds estimated without test outcomes, optional absolute amplification floors, block-structured early representations, calibrated risk scores, and capacity-constrained alerting rules. The proposed framework is evaluated using two open datasets, one focused on crisis rumors and another focused on COVID-19 health misinformation with social engagement information. The results support DDVRI as a probabilistic early-warning and prioritization methodology for rare cases that combine factual risk and high-amplification, rather than as a general fake-news classifier or an automatic moderation system.

This study examines the circulation of disinformation during the 2024 València DANA (high-altitude isolated depression), which produced torrential rainfall across eastern and southern Spain between 29 and 31 October 2024. Using a quantitative content analysis, it analyzes the 100 most viral false or misleading claims, classifying them by typology, format, dissemination channel, and narrative strategy. Findings show an ecosystem dominated by conspiracy narratives about the causes of the disaster and by audiovisual content—particularly short videos and images—which achieved substantially greater reach than textual posts. Narrative mechanisms such as decontextualization, emotional appeal, and political polarization were recurrent and often combined. Verification efforts that matched the original format were associated with higher relative correction reach, although their observable diffusion remained lower than that of the false claims in the analyzed sample. Overall, the study highlights the cross-platform and multimodal dynamics of crisis disinformation and underscores the need for proactive, technologically supported communication strategies. These include automated monitoring, multimodal verification, and interoperable digital infrastructures for crisis communication.

Industrial environments increasingly demand solutions that enable safe, remote and collaborative interaction with physical processes, especially as production systems become more automated, interconnected, and geographically distributed. While digital twins have contributed significantly to monitoring and analysis tasks, they typically lack the immersive, multi-user and interactive capabilities required for advanced supervision and control scenarios. This paper proposes a comprehensive methodology for designing industrial metaverses that extend the concept of digital twins by enabling real-time bidirectional communication with physical automation systems while preserving industrial safety and cybersecurity requirements. The framework integrates a layered communication architecture, a secure command-validation gateway, and an immersive multi-user virtual environment capable of replicating and interacting with a real production process. The methodology is demonstrated through a full case study involving a pick-and-place cell connected to a real Programmable Logic Controller (PLC) via Open Platform Communications Unified Architecture (OPC UA), where a digital twin replaces the physical machine while maintaining identical communication, control logic and safety constraints. The results validate the feasibility of the approach and highlight its potential for remote supervision, operator training, collaborative interaction and experimentation without compromising plant integrity.

Between 2020 and 2024, museums underwent accelerated digital transformation driven by the global health crisis and technological advances, exposing deep inequalities in access to technology and communication capabilities. Museums with limited resources had to rethink their digital strategies to sustain audience engagement and cultural relevance. This article presents a comparative study of museums in Argentina and Spain with restricted budgets, analyzing how they responded to challenges of uncertainty and scarcity. Using a mixed methodology—surveys of 22 professionals, interviews with directors of four representative museums, and qualitative case studies—this study examines the implemented solutions and their impacts. The findings highlight innovative practices grounded in creativity, strategic alliances, and intensive use of social media. Argentine museums excelled in tactical adaptation amid economic instability, while Spanish institutions showed stronger strategic planning. Private museums proved more flexible than their public counterparts, which faced greater bureaucratic constraints. This work contributes to debates on institutional resilience and offers a framework for sustainable digital communication in resource-limited contexts.

Extended-reality (XR) tools are increasingly used to revitalise museum experiences, but typical head-mounted or smartphone solutions tend to fragment audiences and suppress the social dialogue that makes cultural heritage memorable. This article addresses that gap on two fronts. First, it proposes a four-phase design methodology—spanning artifact selection, narrative framing, tangible-interface fabrication, spatial installation, software integration, validation, and deployment—that helps curators, designers, and technologists to co-create XR exhibitions in which co-presence, embodied action, and multisensory cues are treated as primary design goals rather than afterthoughts. Second, the paper reports LanternXR, a proof-of-concept built with the methodology: visitors share a 3D-printed replica of the fourteenth-century Virgin of Boixadors while wielding a tracked “camera” and a candle-like lantern that lets them illuminate, photograph, and annotate the sculpture inside a life-sized Gothic nave rendered on large 4K displays with spatial audio and responsive lighting. To validate the approach, the article presents an analytical synthesis of feedback from curators, museologists, and XR technologists, underscoring the system’s capacity to foster collaboration, deepen engagement, and broaden accessibility. The findings show how XR can move museum audiences from isolated immersion to collective, multisensory exploration.

This study investigates the potential of integrating multilayer animations and sophisticated shader technologies to enhance visitor social interactions within metaverse exhibition spaces. It is part of a broader initiative aimed at developing innovative digital museology strategies that foster social engagement through virtual reality (VR) experiences. The methodology adopted seeks to provide a more immersive and human-centric exploration of 3D digital environments by blending elements of physical spaces with the interactive dynamics common in video games. A virtual exhibition space themed around Mars was created as a testbed to facilitate social interactions among users, who navigate the environment via avatars. This digital space was developed using a specialized Unity template designed by the metaverse platform Spatial.io. Overcoming the programming constraints imposed by Spatial.io, which limits the use of external scripts for security and stability, posed a significant challenge. Nonetheless, by leveraging the ability to modify shader codes used for material creation and employing advanced animation techniques with layered effects, the authors of this work achieved dynamic material responses to lighting changes and initiated complex asset interactions beyond simple linear animations.

This work aims to identify and propose a functional pipeline for indie live-action films using Virtual Production with photorealistic real-time rendering game engines. The new production landscape is radically changing how movies and shows are made. Those were made in a linear pipeline, and now filmmakers can execute multiple tasks in a parallel mode using real-time renderers with high potential for different types of productions. Four interviews of professionals in the Spanish film and television market were conducted to obtain the whole perspective of the new paradigm. Following those examples, a virtual production set was implemented with an Antilatency tracking system, Unreal Engine (version 5.3), and Aximmetry (version 2023.3.2) as the leading software applications. Results are commented on, presenting how all the work is currently closely connected between pre-production, shooting, and post-production and analyzing its potential in different fields.

The presence and significance of artificial intelligence (AI) technology in society have been steadily increasing since 2000. While its potential benefits are widely acknowledged, concerns about its impact on society, the economy, and ethics have also been raised. Consequently, artificial intelligence has garnered widespread attention in news media and popular culture. As mass media plays a pivotal role in shaping public perception, it is crucial to evaluate opinions expressed in these outlets. Understanding the public’s perception of artificial intelligence is essential for effective public policy and decision making. This paper presents the results of a sentiment analysis study conducted on WIRED magazine’s coverage of artificial intelligence between January 2018 and April 2023. The objective of the study is to assess the prevailing opinions towards artificial intelligence in articles from WIRED magazine, which is widely recognized as one of the most reputable and influential publications in the field of technology and innovation. Using two sentiment analysis techniques, AFINN and VADER, a total of 4265 articles were analyzed for positive, negative, and neutral sentiments. Additionally, a term frequency analysis was conducted to categorize articles based on the frequency of mentions of artificial intelligence. Finally, a linear regression analysis of the mean positive and negative sentiments was performed to examine trends for each month over a five-year period. The results revealed a leading pattern: there was a predominant positive sentiment with an upward trend in both positive and negative sentiments. This polarization of sentiment suggests a shift towards more extreme positions, which should influence public policy and decision making in the near future.

This study explores the utilization of Neural Radiance Fields (NeRFs), with a specific focus on the Instant NeRFs technique. The objective is to represent three-dimensional (3D) models within the context of the industrial metaverse, aiming to achieve a high-fidelity reconstruction of objects in virtual environments. NeRFs, renowned for their innovative approach, enable comprehensive model reconstructions by integrating diverse viewpoints and lighting conditions. The study employs tools such as Unity, Photon Pun2, and Oculus Interaction SDK to develop an immersive metaverse. Within this virtual industrial environment, users encounter numerous interactive six-dimensional (6D) models, fostering active engagement and enriching the overall experience. While initial implementations showcase promising results, they also introduce computational complexities. Nevertheless, this integration forms the basis for immersive comprehension and collaborative interactions within the industrial metaverse. The evolving potential of NeRF technology promises even more exciting prospects in the future.