Search Results (207)

Practical training and recruitment strategies are critical for the sustainable implementation of psychosocial interventions. However, few studies have examined how to prepare community partners and doctoral students to support culturally adapted psycho-oncology interventions. This pre-pilot study aims first to evaluate two distinct training programs and recruitment procedures, and second to explore preliminary pre-post outcomes of the Caregiver-Patients Support to Cope with Advanced Cancer (CASA) intervention, using the Consolidated Framework for Implementation Research (CFIR). Three clinical psychology graduate students received CASA training, and two community partners completed Recruitment training. We present descriptive pre- and post-assessments, along with qualitative feedback, for both training and institutional (Puerto Rico Biobank) and community-based recruitment outcomes. A related-samples nonparametric analysis examined pre- and post-CASA intervention signals. Results indicated knowledge gains among doctoral students (pre-test M = 3.3; post-test M = 9.3) and community partners (pre-test M = 4.5; post-test M = 9.5). Preliminary outcomes revealed significant improvements in spiritual well-being (Z = −2.618, p = 0.009) and quality of life (Z = −2.957, p = 0.003) and a reduction in depressive (Z = −2.764, p = 0.006), anxiety (Z = −2.667, p = 0.008), and distress (Z = −2.195, p = 0.028) symptoms following CASA. Of 26 recruited dyads, institutional referrals enrolled 16 dyads (61.5%), while community partners referred 10 dyads with a 90.9% success rate. Findings support the feasibility of both training and CASA exploratory outcomes suggest meaningful psychosocial benefits for Latino dyads coping with advanced cancer. Combining institutional infrastructure with community engagement may enhance sustainability and equitable access to psycho-oncology care. Full article

Generative Artificial Intelligence (GenAI) models produce increasingly sophisticated outputs, yet their underlying mechanisms remain opaque. To clarify how explainability is conceptualized and implemented in GenAI research, this two-stage review systematically examined 261 articles retrieved from six major databases. After removing duplicates and applying predefined inclusion criteria, 63 articles were retained for full analysis. In the first stage, an umbrella review synthesized insights from 18 review papers to identify prevailing frameworks, strategies, and conceptual challenges surrounding explainability in GenAI. In the second stage, an empirical review analyzed 45 primary studies to assess how explainability is operationalized, evaluated, and applied in practice. Across both stages, findings reveal fragmented approaches, a lack of standardized evaluation frameworks, and persistent challenges, including limited generalizability, interpretability–performance trade-offs, and high computational costs. The review concludes by outlining future research directions aimed at developing user-centric, regulation-aware explainability methods tailored to the unique architectures and application contexts of GenAI. By consolidating theoretical and empirical evidence, this study establishes a comprehensive foundation for advancing transparent, interpretable, and trustworthy GenAI systems. Full article

This study aims to review the energy management of microgrids with a structured focus on residential, commercial, and industrial applications. Building on early optimization and control strategies, this study synthesizes advances in forecasting, uncertainty management, computational intelligence, and digital twin integration. Particular attention is given to multi-energy coupling through storage technologies, including hydrogen and thermal pathways, along with life cycle, trilemma, and sustainability considerations. Sector-specific energy management system (EMS) strategies are compared in terms of objectives, methods, and implementation challenges, highlighting both converging and unique requirements across application domains. Cross-sectoral challenges, such as interoperability, cyber-security, resilience valuation, and policy gaps, are analyzed, and emerging research directions, including artificial intelligence (AI)-driven optimization, hierarchical and multi-agent frameworks, and hydrogen-enabled autonomy, are outlined. This review aims to equip researchers, practitioners, and policymakers with a consolidated reference on microgrid EMS, bridging technical innovation with sustainable and resilient energy transitions. Full article

Diabetes self-management education (DSME) programs are evidence-based interventions that improve glycemic control and self-care behaviors, yet their effectiveness may be limited by unaddressed health-related social needs (HRSN) (e.g., food insecurity, housing or utility instability, transportation barriers). This qualitative multiple case study examined the feasibility of integrating HRSN assessments into DSME delivery within three community-based organizations (CBOs) across urban and rural U.S. settings. Guided by the Consolidated Framework for Implementation Research, semi-structured interviews were conducted with 15 DSME facilitators and program leadership to identify contextual factors influencing implementation. Findings revealed that while DSME’s structured, manualized design promotes fidelity and client autonomy, it constrains responsiveness to the client’s HRSN. Facilitators expressed openness to integrating HRSN screening, particularly during intake, yet cited limited infrastructure, role clarity, and training as key barriers. CBOs were recognized as trusted, accessible spaces for holistic care, but growing expectations to address HRSN without adequate resources for referral created sustainability concerns. Participants recommended a parallel support model involving navigators or community health workers to manage HRSN screening and referrals alongside DSME sessions. Integrating HRSN assessment processes into DSME may enhance engagement, reduce attrition, and extend the reach of diabetes education to populations most affected by HRSN. However, successful implementation requires dedicated funding, workforce development, and cross-sector coordination. Findings underscore the importance of supporting CBOs as critical partners in bridging diabetes education and social care to advance whole-person, chronic disease management. Full article

This study explores the potential of educational game design as a pedagogical strategy for teaching Mathematics in lower secondary education, addressing persistent challenges related to students’ motivation and engagement with the subject. The research focuses on the creation and implementation of a game, CriaMat, an ideation tool developed to support students in designing their own mathematical games. A qualitative approach was adopted, structured as a case study conducted in four classes and involving a total of 50 students. Data collection followed a mixed-methods strategy, combining participant observation, document analysis, and questionnaire-based inquiry, each applied during different phases of the intervention. The results indicate a positive reception of the approach, particularly in terms of student engagement, collaboration, and perceived learning. Analysis of the games produced demonstrates students’ ability to create functional games that integrate the knowledge and skills developed throughout the process. The findings also suggest that learning to design games was perceived as a valuable strategy for engaging with and consolidating mathematical content, while simultaneously providing a privileged context for developing essential competencies—such as critical thinking, creativity, and problem-solving—aligned with the national competency framework for compulsory education. The study does not aim to measure learning gains, but rather to explore students’ perceptions and experiences of learning mathematics through the process of game creation. Full article

Targeted next-generation sequencing (tNGS) closes the gap between point-of-care rapid tests and phenotypic drug susceptibility testing (pDST) in drug-resistant tuberculosis (DR-TB). The 2025 World Health Organization (WHO) consolidated guidelines and the operational handbook place tNGS after initial automated nucleic acid amplification tests (aNAATs) for the delivery of catalogue-linked molecular drug susceptibility testing (DST) for a broad drug panel, reserving whole-genome sequencing (WGS) and/or pDST for discordance resolution, confirmation, and surveillance. This review summarizes (i) the core tNGS principles and panel design; (ii) platform-specific workflows for Illumina and Nanopore, including direct-from-sample implementations and typical turnaround times; (iii) catalogue-based interpretation against the 2023 WHO Mycobacterium tuberculosis mutation catalogue, with emphasis on bedaquiline/clofazimine (BDQ/CFZ) resistance and management of uncertain variants; (iv) pooled accuracy and sources of genotype–phenotype discordance; and (v) practical requirements for bioinformatics, quality assurance/external quality assessment (QA/EQA), and standardized reporting. We summarize operational and economic considerations (throughput, batching, and network design) to clarify where tNGS adds value compared with alternative strategies and to outline priority research needs, including (i) performance standards for culture-free tNGS, (ii) robust heteroresistance detection, (iii) standardized variant curation, and (iv) data-sharing frameworks to refine genotype–phenotype links. When embedded within validated QA/EQA frameworks and catalogue-linked reporting systems, tNGS can shorten the time to effective therapy by rapidly informing fluoroquinolone (FQ) susceptibility and providing early, tiered resistance signals for newer agents (e.g., BDQ), with indeterminate findings prompting reflex pDST/WGS. Full article

Background/Objectives: This study explores the perceptions, experiences, and expectations of pediatric healthcare professionals regarding the implementation of virtual visits (VVs) in routine pediatric practice. Methods: Using the Consolidated Framework for Implementation Research (CFIR) to analyze individual, organizational, and contextual factors influencing the adoption of pediatric virtual visits, we conducted a descriptive cross-sectional survey distributed nationwide among pediatricians, pediatric nurses, and residents. Results: A total of 308 Spanish healthcare professionals correctly completed the REDCap survey and were included in the analysis. The mean age was 44.3 years, and respondents represented both hospital-based (55.8%) and primary care professionals (44.2%). Overall, 74.8% had previous experience with telephone consultations, while only 11% had performed virtual visits. Most professionals believed VVs could be useful in primary care (81.3%) and hospital out-patient settings (73.9%), especially for follow-up appointments, communication of test results, and chronic-care monitoring. VVs were perceived as more appropriate for older children and adolescents than for infants. Major concerns included poor internet connection (52.6%), and data security (37.4%); however, a particularly relevant finding was the low confidence in using digital tools, particularly among older professionals. Comparative analyses by age and workplace setting identified differences in interest, perceived barriers, and access to technical resources. Hospital-based clinicians reported greater interest in adopting VVs and better access to technological resources compared with primary care professionals. The professionals’ age was inversely associated with interest in VVs. Notably, 72.6% of respondents expressed interest in receiving specific VV training, and nearly 90% believed virtual visits should be offered in their workplace. Conclusions: These findings show a high overall acceptance of VVs but also underline persistent barriers related to infrastructure, digital literacy, and clinical applicability in younger children. Addressing these obstacles through training, improved equipment, and clear clinical protocols will be essential for the successful implementation of pediatric VV programs. Full article

Social housing plays a key role in the Colombian residential market, showing a growing commitment to sustainability: currently, a high percentage of EDGE-certified homes belong to this segment. However, in hot and humid areas such as Montería, most VIS homes have deficiencies in their thermal envelopes and poor roof insulation, which leads to a heavy reliance on air conditioning. This study addresses the lack of practical and replicable methodologies for improving energy efficiency in social housing located in hot–humid climates. The research aims to develop and apply a methodological framework that integrates architectural rehabilitation strategies with quantitative evaluation using the EDGE App tool. The proposed approach was implemented in Montería, Colombia, through a case study that combines diagnostic analysis of existing housing conditions, simulation of energy-saving measures, and assessment of environmental and economic performance. A real home in Montería was used as a reference, and more than 600 simulations were carried out considering different orientations and passive strategies. Through a Pareto analysis, the three most efficient measures were identified: natural ventilation, high-solar-reflectance roofing, and moderate reduction in the U-value. Together, these measures reduced energy consumption by up to 50%, with minimal increases in construction costs (≤1.2% of the commercial value). It was also found that excessive insulation can induce unwanted nighttime heating demands, highlighting the need for adjustments to the climatic context. The results confirm the technical and economic feasibility of mass rehabilitation of VIS in hot and humid climates using standard passive measure packages, consolidating the role of the EDGE App as a key tool for guiding sustainable design, investment, and environmental certification decisions. Full article

This Editorial presents an integrative overview of the Special Issue “Advanced Autonomous Systems and Artificial Intelligence Stage”, which assembles fifteen peer-reviewed articles dedicated to the recent evolution of AI-enabled and autonomous systems. The contributions span a broad spectrum of domains, including renewable energy and power systems, intelligent transportation, agricultural robotics, clinical and assistive technologies, mobile robotic platforms, and space robotics. Across these diverse applications, the collection highlights core research themes such as robust perception and navigation, semantic and multi modal sensing, resource-efficient embedded inference, human–machine interaction, sustainable infrastructures, and validation frameworks for safety-critical systems. Several articles demonstrate how physical modeling, hybrid control architectures, deep learning, and data-driven methods can be combined to enhance operational robustness, reliability, and autonomy in real-world environments. Other works address challenges related to fall detection, predictive maintenance, teleoperation safety, and the deployment of intelligent systems in large-scale or mission-critical contexts. Overall, this Special Issue offers a consolidated and rigorous academic synthesis of current advances in Autonomous Systems and Artificial Intelligence, providing researchers and practitioners with a valuable reference for understanding emerging trends, practical implementations, and future research directions. Full article

The aviation industry faces increasing pressure to reduce its environmental impact and achieve net-zero emissions by 2050. In this context, sustainable aviation fuels (SAF) have emerged as a critical alternative to conventional jet fuels. This study provides a comprehensive analysis of SAF technologies from a chemical engineering perspective, highlighting key production routes, technological maturity levels, and implementation challenges. A bibliometric analysis using the Scopus database and VOSviewer software was conducted to identify research trends and thematic clusters in SAF literature. The analysis reveals a growing interest in advanced biofuels and physicochemical conversion technologies, particularly those supported by catalytic and thermochemical processes. Certified and emerging SAF pathways were examined with respect to their process efficiency, feedstock availability, and scalability. Additionally, the study explores the potential of Latin America as a strategic region for SAF development, considering its abundant biomass resources and ongoing pilot projects. This critical and holistic analysis aims to support researchers, engineers, and policymakers in understanding the current state and future directions of SAF technologies within the framework of chemical process design and optimization. Overall, Hydroprocessed Esters and Fatty Acids Synthetic Paraffinic Kerosene (HEFA-SPK) and Fischer–Tropsch Synthetic Paraffinic Kerosene (FT-SPK) are identified as the most mature and widely deployed SAF production routes, whereas Alcohol to Jet (ATJ), Synthesized Iso-Paraffins (SIP), and Direct Sugar to Hydrocarbons (DSHC) remain at earlier technological stages despite their long-term potential for feedstock diversification and reduced environmental impacts. The analysis also underscores Latin America, where abundant biomass resources, consolidated agro-industrial systems, and emerging SAF research initiatives create favorable conditions for future development and deployment. Full article

Background: Community-Based Participatory Research (CBPR) has proven effective in promoting health research in hard-to-recruit and underserved populations. Tai Chi Prime is a National Council on Aging-certified fall prevention program. However, it has not been widely disseminated in African American (AA)/Black and Latinx communities. Guided by the Consolidated Framework for Implementation Research (CFIR), this study examined the process of working with a community advisory board (CAB) to adapt and disseminate Tai Chi Prime within these communities, as well as facilitators and barriers to CAB success. Methods: Eight CAB members met with researchers monthly virtually over a two-year period. Meetings focused on reviewing Tai Chi Prime materials, discussing cultural adaptations, and identifying dissemination strategies relevant to AA/Black and Latinx communities. Detailed notes from 24 meetings were compiled. In addition, semi-structured interviews were conducted with five CAB members and two researchers to capture individual reflections on their experiences, roles, and perceived impact. Data was analyzed using directed content analysis. Results: CFIR constructs helped illuminate how CAB members’ embedded community expertise, organizational partnerships, available resources, shared vision and transparent communication influenced the cultural adaptation and dissemination of Tai Chi Prime. Study findings also highlight important areas that extend beyond CFIR, particularly the cultural knowledge and power-sharing responsibilities undertaken by CAB members as co-researchers. These insights underscore the need to integrate equity-focused and community-engaged research principles into implementation frameworks when working with communities of color. Conclusions: Findings highlight the value of leveraging existing academic–community partnerships. Community-engaged researchers can use the lessons learned from this CAB to build a replicable model of sustainable partnerships with their AA/Black and Latinx community partners, as can others involved in health services research and policy. Full article

The findings of this Systematic Review suggest that Green Social Work (GSW) is gaining momentum as a framework that integrates environmental sustainability with social and relational justice. In the context of climate emergencies and deepening socio-environmental inequalities, GSW proposes a transformative vision for professional practice and highlights the need to rethink the role of social work in addressing ecological challenges. This article presents a systematic review of academic literature aimed at analyzing the conceptual development, areas of application, and methodological characteristics of GSW. Fifteen peer-reviewed articles were selected through a structured search in five international databases, applying inclusion criteria that required explicit reference to the GSW framework. The review examines how GSW has been implemented in practice, education, community intervention, and policy design. The findings point to emerging patterns in the application of GSW across contexts of environmental vulnerability, such as disaster recovery, rural development, and climate justice, as well as its incorporation into professional training and ethical codes. However, the review also reveals the absence of shared operational definitions and the predominance of qualitative, exploratory studies with limited generalizability. Overall, GSW offers a valuable pathway for strengthening the contribution of social work to ecological and social challenges. Its integration into education, research, and policy can enhance professional responses to complex crises, although clearer operational frameworks and more robust empirical studies are needed to consolidate GSW as a key tool for socio-environmental transformation. Full article

Air quality prediction is a critical challenge amid rising environmental and health risks from pollution. This study conducts a systematic literature review (SLR) to compare traditional statistical models and machine learning (ML) techniques applied to air quality forecasting. Following the PRISMA 2020 protocol, 412 peer-reviewed articles (2016–2025) were analyzed using thematic filters and bibliometric tools. Results show a marked shift toward ML methods, particularly in Asia (73.2%), with limited representation from Latin America and Africa. Statistical models focused mainly on MLR (88.6%) and ARIMA (11.4%), while ML approaches (n = 574) included Random Forest, LSTM, and SVM. Only 12% of studies conducted direct comparisons. A total of 1177 predictor variables and 307 performance metrics were systematized, highlighting PM2.5, NO₂, and RMSE. Hybrid models like CNN-LSTM show strong potential but face challenges in implementation and interpretability. This review proposes a consolidated framework to guide future research toward more explainable, adaptive, and context-aware predictive models. Full article

This study develops and empirically validates a theoretical model designed to assess the performance of tourism innovation ecosystems by integrating the dimensions of innovation, technology, and sustainability—dimensions that have typically been examined in isolation within the literature. The empirical investigation was conducted at two major tourism destinations: a pilot phase in Las Vegas, followed by the main study in Orlando, USA. Data collection was facilitated via the Amazon Mechanical Turk (MTurk) platform, and analysis was conducted using Confirmatory Factor Analysis (CFA) and Structural Equation Modeling (SEM), enabling the examination of eight hypotheses across seven constructs. The findings provided evidence of both convergent and discriminant validity and supported five of the eight proposed hypotheses. Specifically, the study confirmed significant relationships among technology acceptance and adoption, adoption and innovation generation, innovation and both sustainability and overall ecosystem performance, and adoption and sustainability. Conversely, collaboration and actor-integration barriers did not exhibit significant effects in Orlando, which is consistent with its mature institutional environment. Innovation emerged as a mediating variable linking technology and sustainability, exerting a substantial influence on overall ecosystem performance. This research advances the theoretical consolidation of the tourism innovation ecosystem concept and offers actionable insights for destination managers aiming to foster innovation, facilitate the adoption of connective technologies, and implement sustainable strategies. The proposed model demonstrates empirical robustness and practical relevance, providing a comprehensive framework for analyzing and enhancing smart, resilient tourism destinations. Full article

Modified tuber starches have gained relevance as innovative and versatile materials for the encapsulation of bioactive compounds, distinguishing themselves from synthetic polymers due to their biocompatibility, biodegradability, and tunable functionality. This review analyzes the effects of physical, chemical, and biochemical modifications on the composition and morphological, rheological, thermal, and techno-functional properties of tuber starches, as well as their development prospects as coating materials in encapsulation techniques such as spray drying, freeze-drying, electrospinning, and emulsification. The evidence reviewed indicates that modified tuber starches exhibit reduced retrogradation, higher thermal resistance, improved solubility, and better digestibility, facilitating their application as protective agents. The main challenges for their industrial implementation are identified and analyzed, including the standardization of processes, scalability, and the ambiguous regulatory framework. In the future, research in this area should be directed toward the optimization of “clean-label” methodologies and the valorization of non-conventional tuber sources, thereby consolidating the development of safer, more effective, and more sustainable encapsulation systems for the food industry. Full article