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This paper reviews the methodology used by the World Economic Forum (WEF) to create the Global Competitiveness Index (WEF-GCI). We propose an alternative competitiveness index that only includes the objective data (hard data) from the WEF-GCI and is created by applying a multivariate statistical procedure (Exploratory Factor Analysis) that allows us to determine the weights from the implicit data structure. The rankings obtained from this index have a high degree of association with those provided by the WEF. The main benefit of this index over the WEF index is that it does not include valuations from opinion surveys given to business executives and/or entrepreneurs of the countries included in the index (soft data). Consequently, the rankings from this alternative index are not affected by political biases or individual interests as it is elaborated only including officially published objective data.

The aim of this research is to investigate tourist marketing within the embryonic context of the metaverse in order to comprehend the building blocks and the primary technologies employed in the sector. A systematic literature review (SLR) was conducted on 386 articles, with an overall qualitative approach that included 86 references, all of which dealt with the topic of the metaverse and had direct or potential implications for the tourism sector (hotels, restaurants, means of transport, leisure activities and destination itself). The articles are taken from: Science Direct, Taylor & Francis, Emerald, Springer and Google Scholar. The SLR was carried out according to the PRISMA search protocol. The results indicate the technologies that have been most thoroughly studied at the confluence of marketing, tourism, and the metaverse (AI, virtual reality, augmented reality, mixed reality, blockchain, tokens (NFTs) and digital twins). Moreover, they establish the foundational components of tourism marketing in the metaverse for the first time (tourism products, the metaverse as a distribution and branding channel for tourism and, tourist customer as protagonist). Finally, the study exposes research gaps and recommends future directions for exploration (monetization of products in the metaverse, promotion and marketing strategies in the metaverse, new profiles for marketing professionals, policy development that regulates commercial activity in the metaverse).

As an emerging learning method, mobile technologies allow students to gain knowledge via both formal and informal learning. In spite of the advantages mobile technologies bring to education, its adoption for learning purposes has not been encouraging. Existing research on mobile learning acceptance has been mainly focused on technological and use issues, while the topic of student learning beliefs has been researched less often. The current study addresses said research gap by examining the influence of constructivist and traditional learning beliefs on university students’ intentions to use mobile learning in China and Spain. In addition, cultural differences were also tested in this study. The results of this study support the validity of the proposed model in the two samples (China and Spain) and provide evidence of the importance of learning beliefs as an antecedent of perceived usefulness and perceived compatibility.

Chronic pain remains a major problem worldwide, despite the availability of various non-pharmacological and pharmacological treatment options. Therefore, new analgesics with novel mechanisms of action are needed. Monoclonal antibodies (mAbs) are directed against specific, targeted molecules involved in pain signaling and processing pathways that look to be very effective and promising as a novel therapy in pain management. Thus, there are mAbs against tumor necrosis factor (TNF), nerve growth factor (NGF), calcitonin gene-related peptide (CGRP), or interleukin-6 (IL-6), among others, which are already recommended in the treatment of chronic pain conditions such as osteoarthritis, chronic lower back pain, migraine, or rheumatoid arthritis that are under preclinical research. This narrative review summarizes the preclinical and clinical evidence supporting the use of these agents in the treatment of chronic pain.

Predicting mass migration is one of the main challenges for policymakers and NGOs working with migrants worldwide. Recently there has been a considerable increase in the use of computational techniques to predict migration flows, and advances have allowed for application of improved algorithms in the field. However, given the rapid pace of technological development facilitating these new predictive tools and methods for migration, it is important to address the extent to which such instruments and techniques engage with and impact migration governance. This study provides an in-depth examination of selected existing predictive tools in the migration field and their impact on the governance of migratory flows. It focuses on a comparative qualitative examination of these tools’ scope, as well as how these characteristics link to their respective underlying migration theory, research question, or objective. It overviews how several organisations have developed tools to predict short- or longer-term migration patterns, or to assess and estimate migration uncertainties. At the same time, it demonstrates how and why these instruments continue to face limitations that in turn affect migration management, especially as it relates to increasing EU institutional and stakeholder efforts to forecast or predict mixed migration. The main predictive migration tools in use today cover different scopes and uses, and as such are equally valid in shaping the requirements for a future, fully comprehensive predictive migration tool. This article provides clarity on the requirements and features for such a tool and draws conclusions as to the risks and opportunities any such tool could present for the future of EU migration governance.

Instruments to measure self-determination have only been available in the Spanish language to date, for adolescents with intellectual disability (ID). However, given the development of a new measure of self-determination for youth with and without disabilities, the Self-Determination Inventory, there is a need to adapt and validate this tool in the Spanish language so as to provide practitioners with a psychometrically strong measure of self-determination. This study provides evidence of reliability and validity of the Spanish version of the scale, empirically tested with a sample of 620 youth with and without disabilities in Spain. Specifically, validity was evidenced through structural equation modeling approaches, confirming the instrument adequacy to measure self-determination in Spanish speaking youth. Future lines of research are suggested.

Reducing carbon dioxide (CO 2 ) emissions urgently requires the large-scale deployment of carbon-capture technologies. These technologies must separate CO 2 from various sources and deliver it to different sinks 1 , 2 . The quest for optimal solutions for specific source–sink pairs is a complex, multi-objective challenge involving multiple stakeholders and depends on social, economic and regional contexts. Currently, research follows a sequential approach: chemists focus on materials design 3 and engineers on optimizing processes 4 , 5 , which are then operated at a scale that impacts the economy and the environment. Assessing these impacts, such as the greenhouse gas emissions over the plant’s lifetime, is typically one of the final steps 6 . Here we introduce the PrISMa (Process-Informed design of tailor-made Sorbent Materials) platform, which integrates materials, process design, techno-economics and life-cycle assessment. We compare more than 60 case studies capturing CO 2 from various sources in 5 global regions using different technologies. The platform simultaneously informs various stakeholders about the cost-effectiveness of technologies, process configurations and locations, reveals the molecular characteristics of the top-performing sorbents, and provides insights on environmental impacts, co-benefits and trade-offs. By uniting stakeholders at an early research stage, PrISMa accelerates carbon-capture technology development during this critical period as we aim for a net-zero world. A framework that integrates materials, process design, techno-economics and life-cycle assessment can be used to accelerate the development of carbon-capture technology as we aim for a net-zero world.

This study aims to find out how the groups that form the education community (students, teachers, families) differ in terms of the various characteristics surrounding the cyberbullying phenomenon. To do this, we conducted research using a selective correlational and cross-sectional design to analyze relationships and differences among variables: defining cyberbullying, typology, involved roles, possible causes and coping strategies in the different groups. The study recruited 116 participants as follows: 51% were year-6 Primary Education students; 29% were students’ family members; 20% were school teachers. We collected data through an ad hoc questionnaire that a group of experts had previously validated. The results of the data analysis showed that significant differences appeared in terms of: how typologies were perceived; the importance of roles; coping strategies for cyberbullying.

Post-COVID cardiac complications have emerged as a significant and persistent clinical concern, yet their underlying mechanisms remain poorly understood. Animal models can act as proxies to investigate the pathophysiology of the human, post-acute sequelae of SARS-CoV-2 infection (PASC). The aim of this experimental study was to evaluate the expression of inflammatory biomarkers in cardiac tissue 28 days after SARS-CoV-2 infection in a female hACE2 mouse model, with a focus on chemokine-mediated immune activation. Twelve female C57BL/6 hACE2 mice were infected with the Omicron variant (BA.1.17 lineage) of SARS-CoV-2, and eleven non-infected mice served as controls. Cardiac tissue was analyzed via Western blot for markers of innate immune activation (TLR4, MyD88, NF-κB) and pro-inflammatory cytokines (IL-6, IL-18, IL-1β, TNF-α, CD11d). Cardiac tissue injury markers (iNOS, PAI-1 and Connexin43) were also analyzed. Compared to non-infected mice, cardiac tissue from infected mice showed significantly higher expression of IL-6 (p = 0.028), indicating an inflammatory state, and CD11d (p = 0.016), suggesting an inflammatory stage accompanied by sustained activation of chemokine-mediated inflammatory signaling. No significant differences in TLR4 (p = 0.340), MyD88 (p = 0.410), NF-κB p65 (p = 0.780), IL-18 (p = 0.548), IL-1β (p = 0.455), and TNF-α (p = 0.125) expressions were observed Similarly, no changes in cardiac damage markers (iNOS: p = 0.4684; PAI-1: p = 0.5345; Connexin 43: p = 0.2879) were found. The results of this experimental study would support the hypothesis of persistent low-grade inflammation as a contributor to post-COVID cardiac sequelae in females that is not accompanied by severe tissue damage, as also observed in clinical studies. This study also reinforces the need for studies evaluating the functional and structural evolution of the myocardium after an acute SARS-CoV-2 infection.

Within the Energy Performance of Buildings Directive information symmetry regarding financial and environmental benefits, coming from real estate performance, is a key element in the promotion of efficient buildings. However, the link between energy efficiency and its perceived co-benefits is far from perfect in EU countries with a short trajectory in the promotion of such residential attributes, endangering the efficacy of information-symmetry policies. Using a large survey applied to sellers, buyers, lessors and tenants this paper explores, in Spain, the perceived co-benefits in terms of energy savings and thermal comfort of efficient homes and whether such perception correlates to current living conditions, housing tenure and sociodemographic profile of respondents. Results suggest that in general such co-benefits are present in the mind of the main agents of the housing market. However, their perception is far from being homogeneous, it is clearer in the case of households whose current home is poorly insulated or inadequately serviced in terms of thermal active systems. Sociodemographic conditions also play a role in co-benefits perceptions: Elder, wealthier and landlords, irrespective of whether they act as sellers, buyers or lessors, do perceive to a larger extent the co-benefits of efficient homes. Such findings signal clear paths for the improvement of energy and housing policy.