Search Results (3,063)

Working memory capacity (WMC) has long served as a central indicator of individual differences in complex cognition. However, growing evidence suggests that a substantial portion of its predictive power may reflect attention control (AC)—including goal maintenance, interference management, and inhibition—rather than storage capacity alone. This review synthesizes findings across six domains: (1) perception and sensory discrimination, (2) learning and problem solving, (3) cognitive control and decision making, (4) retrieval and memory performance, (5) multitasking and real-world performance, and (6) clinical applications. Across these areas, WMC-related effects frequently align with demands on AC, though the strength and nature of this alignment vary by domain. We highlight the importance of incorporating reliable AC measures and recommend latent-variable approaches to more clearly separate storage, control, and representational processes underlying complex performance. Full article

Against the backdrop of China’s dual-carbon goals and the global push toward net-zero emissions, Macao faces not only an innovation deficit but also the urgent need to reconfigure its economic structure toward green and low-carbon development. This study investigates collaborative innovation mechanisms within Macao’s technological ecosystem through the lens of new qualitative productivity, a paradigm emphasizing structural optimization and systemic innovation capacity. As a micro-jurisdiction within the Guangdong–Hong Kong–Macao Greater Bay Area (GBA), Macao faces challenges due to its tourism-dependent economy and spatial constraints. Employing a qualitative methodology grounded in collaborative governance theory, the research combines theoretical framework construction with empirical case studies of technology enterprises, notably Enterprise B, to analyze stakeholder interactions, resource integration, and institutional dynamics. This study examines how collaborative technological innovation governance in a micro-jurisdiction can underpin net-zero and green supply chain transitions by mobilizing cross-border resources and institutional synergies. Key findings reveal a polycentric governance model involving government, enterprises, academic institutions, and civil society organizations. This model leverages cross-border synergies, platformization, and adaptive recalibration to overcome structural limitations. Results highlight tripartite drivers—policy incentives, market forces, and corporate strategies—that enhance innovation throughput. Despite advancements in institutional coordination, challenges persist, including low enterprise absorption of government funding, talent attrition, and fragmented academic–industrial linkages. The study proposes strategic recalibrations, such as refining policy architectures, strengthening industry–academia–research symbiosis, and optimizing transnational collaboration through Macao’s Lusophone networks. The findings provide governance insights for micro-jurisdictions seeking to align new qualitative productivity with decarbonization, renewable energy integration, and participation in regional green supply chains. Full article

The objective of the study was to propose curricular guidelines for environmental literacy from a sustainability perspective for the Universidad de la Amazonia distance and virtual programs. The research adopted a mixed-methods approach, with a critical, analytical, and interpretive methodological design structured into three phases: a document review, an exploration of teachers’ and students’ perspectives, and a proposal phase. The results revealed significant weaknesses in the curricular integration of environmental education in virtual and distance learning programs, which limit their effective contribution to achieving the Sustainable Development Goals (SDGs). Likewise, the need to strengthen students’ critical thinking, territorial commitment, and transformative action was identified as a key competency for promoting educational practices oriented toward sustainability, socio-environmental responsibility, and decision-making aligned with national environmental policies and the 2030 Agenda. Based on these findings, guidelines were proposed that articulate pedagogical, didactic, and evaluative components, with recommendations for their practical application in design, implementation, and evaluation, to consolidate contextualized environmental literacy that is relevant and consistent with the socio-environmental challenges of the Amazon region. Full article

AI-driven imaging is becoming central to crop monitoring, with proximal and unmanned aerial vehicle (UAV) platforms now routinely used for disease and stress detection, yield estimation, canopy structure, and fruit counting. Yet, as these models move from plots to farms, the main bottleneck is no longer raw accuracy but robustness under distribution shift. Systems trained in one field, season, cultivar, or sensor often fail when the scene, sensor, protocol, or timing changes in realistic ways. This review synthesizes recent advances on robustness and transferability in proximal and UAV imaging, drawing on a corpus of 42 core studies across field crops, orchards, greenhouse environments, and multi-platform phenotyping. Shift types are organized into four axes, namely scene, sensor, protocol, and time. The article also maps the empirical evidence on when RGB imaging alone is sufficient and when multispectral, hyperspectral, or thermal modalities can potentially improve robustness. This serves as a basis to synthesize acquisition and evaluation practices that often matter more than architectural tweaks, which include phenology-aware flight planning, radiometric standardization, metadata logging, and leave-one-field/season-out splits. Adaptation options are consolidated into a practical symptom/remedy roadmap, ranging from lightweight normalization and small target-set fine-tuning to feature alignment, unsupervised domain adaptation, style translation, and test-time updates. Finally, a benchmark and dataset agenda are outlined with emphasis on object-oriented splits, cross-sensor and cross-scale collections, and longitudinal datasets where the same fields are followed across seasons under different management regimes. The goal is to outline practices and evaluation protocols that support progress toward deployable and auditable systems, noting that such claims require standardized out-of-distribution testing and transparent reporting as emphasized in the benchmark specification and experiment suite proposed here. Full article

In regions with abundant solar energy, solar water disinfection (SODIS) offers a sustainable strategy to improve drinking water access, especially in rural, off-grid communities. This study presents a numerical modeling approach to assess the thermal and microbial disinfection performance of glass-free parabolic trough collectors (PTCs). The model integrates geometric sizing, one-dimensional thermal energy balance, and first-order microbial inactivation kinetics, supported by optical simulations in SolTRACE 3.0. Simulations applied to a representative case in the Colombian Caribbean (Gambote, Bolívar) highlight the influence of rim angle, focal length, and optical properties on system efficiency. Results show that compact PTCs can achieve fluid temperatures above 70 °C and effective pathogen inactivation within short exposure times. Sensitivity analysis identifies key geometric and environmental factors that optimize performance under variable conditions. The model provides a practical tool for guiding the design and local adaptation of SODIS systems, supporting decentralized, low-cost water treatment solutions aligned with sustainable development goals. Furthermore, it offers a framework for future assessments of PTC implementations in different climatic scenarios. Full article

Background: This study examined how patients and caregivers perceive and experience AI-based care technologies through text mining analysis. The goal was to identify major themes, sentiments, and value-oriented interpretations embedded in their narratives and to understand how these perceptions align with key dimensions of patient-centered care. Methods: A corpus of publicly available narratives describing experiences with AI-based care was compiled from online communities. Natural language processing techniques were applied, including descriptive term analysis, topic modeling using Latent Dirichlet Allocation, and sentiment profiling based on a Korean lexicon. Emergent topics and emotional patterns were mapped onto domains of patient-centered care such as information quality, emotional support, autonomy, and continuity. Results: The analysis revealed a three-phase evolution of care values over time. In the early phase of AI-mediated care, patient narratives emphasized disruption of relational care, with negative themes such as reduced human connection, privacy concerns, safety uncertainties, and usability challenges, accompanied by emotions of fear and frustration. During the transitional phase, positive themes including convenience, improved access, and reassurance from diagnostic accuracy emerged alongside persistent emotional ambivalence, reflecting uncertainty regarding responsibility and control. In the final phase, care values were restored and strengthened, with sentiment patterns shifting toward trust and relief as AI functions became supportive of clinical care, while concerns related to depersonalization and surveillance diminished. Conclusions: Patients and caregivers experience AI-based care as both beneficial and unsettling. Perceptions improve when AI enhances efficiency and information flow without compromising relational aspects of care. Ensuring transparency, explainability, opportunities for human contact, and strong data protections is essential for aligning AI with principles of patient-centered care. Based on a small-scale qualitative dataset of patient narratives, this study offers an exploratory, value-oriented interpretation of how relational care evolves in AI-mediated healthcare contexts. In this study, care-ethics values are used as an analytical lens to operationalize key principles of patient-centered care within AI-mediated healthcare contexts. Full article

This study examines the effectiveness and implementation fidelity of the Mind–Grit Pathways framework, a blended and personalized learning intervention integrating academic instruction with growth mindset and grit development in alignment with Sustainable Development Goal 4 (Quality Education). Using a quasi-experimental pretest–posttest control group design, the study analyzed Grade 11 students from two demographically comparable urban high schools (n = 933). Treatment students (n = 491) participated in the intervention across mathematics, science, and English/reading for one academic year, while control students received traditional instruction. Multivariate analyses indicated significantly greater academic gains for treatment students across all subject areas and total achievement (p < 0.001). Within the treatment group, substantial teacher- and homeroom-level variation was observed, with large effects in mathematics and moderate effects in science and English/reading, highlighting the role of instructional enactment. Teacher professional development hours were positively associated with student engagement and achievement gains, and student platform usage demonstrated a strong relationship with academic growth, providing objective evidence of implementation fidelity. The results suggest that blended learning frameworks can produce meaningful and equitable academic gains when supported by sustained professional development and high-quality classroom implementation. Full article

The Agenda 2030 for Sustainable Development was adopted by the United Nations (UN) to guide action towards sustainable development for humanity at every scale, as “Leave no one behind” is the central, transformative promise of the agenda. The 17 global Sustainable Development Goals (SDGs) provide ambitious political targets for every UN member state to shape the future univocally. However, the sustainability challenges faced at regional and subnational levels, e.g., community levels, are substantially diverse and the strategies for achieving the SDGs also vary across communities based on their context, agency and resources. We developed a pluralistic framework to guide policy action and grass-root transformation at every scale, aligning with the global SDGs, by systematically reviewing 79 sustainability transformation projects reported in the published literature. We analyzed what these diverse scale projects had in common regarding sustainability strategies, collaborations among societal actors and how new narratives were transferred into guided action. The framework comprises five consequent phases for the implementation of SDGs and SDG targets through problem formulation to project evaluation and four enabling factors comprising context, temporality, disciplines and stakeholders that crucially facilitate the implementation of SDGs and SDG targets. Our framework pursues the “leave no scale behind” aspiration, focusing on multi-stakeholder processes and inter- and transdisciplinary methods to strengthen collaboration among a diverse set of actors, joint learning, and coherent implementation across all relevant areas of society. Full article

A hybrid machine learning framework has been developed in this study to estimate Terrestrial Water Storage Anomalies (TWSA) in Morocco’s Casablanca–Settat region, which faces serious groundwater stress due to rapid urbanization, intensive agriculture, and climate variability. In this study, TWSA is used as an integrated proxy for groundwater-related storage changes, while acknowledging that it also includes contributions from soil moisture and surface water. The approach combines satellite-based observations from the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (GRACE-FO) with key environmental indicators such as rainfall, evapotranspiration, and land use data to track changes in groundwater availability with improved spatial detail. After preprocessing the data through feature selection, normalization, and outlier handling, the model applies six base learners, i.e., Huber regressor, automatic relevance determination regression, kernel ridge, long short-term memory, k-nearest neighbors, and gradient boosting. Their predictions are aggregated using a random forest meta-learner to improve accuracy and stability. The ensemble achieved strong results, with a root mean square error of 0.13, a mean absolute error of 0.108, and a determination coefficient of 0.97—far better than single-model baselines—based on a temporally independent train-test split. Spatial analysis highlighted clear patterns of groundwater depletion linked to land cover and usage. These results can guide targeted aquifer recharge efforts, drought response planning, and smarter irrigation management. The model also aligns with national goals under Morocco’s water sustainability initiatives and can be adapted for use in other regions with similar environmental challenges. Full article

Childhood malnutrition remains a pressing public health challenge in Europe, where stunting, wasting, and underweight coexist with rising rates of childhood overweight and obesity. This policy review provides a strategic roadmap for promoting healthy nutrition in early childhood by synthesizing WHO and EU guidance and proposing coordinated action across three time horizons. Short-term goals (1–3 years) include harmonizing food-based dietary guidelines, implementing universal nutrition screening in pediatric care, and strengthening breastfeeding-supportive environments. Mid-term priorities (3–7 years) focus on fiscal levers, such as sugar taxes and healthy food subsidies; reformulating children’s products; and embedding nutrition education within school curricula. Long-term strategies (7+ years) emphasize harmonized EU-wide monitoring systems, alignment of early-life nutrition with social protection policies, and sustained investment in research on the DOHaD. Through a unified, multisectoral strategy emphasizing early-life nutrition, equitable access to healthy foods, education, and robust regulation, Europe can effectively address the double burden of malnutrition and sustainably reduce childhood obesity. Full article

Ankle injuries are among the most common sports injuries in basketball and represent a substantial public health and economic burden. This narrative review synthesises evidence on ankle bracing as external protective support and shows that ankle braces reduce the risk of both first-time injuries and ankle re-injuries in basketball players without significantly affecting sport-specific performance, such as sprinting, jumping, or changing direction. Similarly, despite earlier theoretical concerns, current evidence shows no increased risk of knee injury associated with the use of ankle bracing. Mechanistic studies indicate that protection is provided by limiting excessive frontal-plane motion, enhancing proprioceptive feedback, and increasing perceived joint stability. Economic analyses show that a single ankle injury generates considerable direct and indirect costs, whereas seasonal team-wide ankle bracing programmes are low cost per athlete and likely cost-effective at scale. As a public health measure, ankle bracing is practical and easily scalable in community and sports settings. Overall, routine ankle bracing is shown to be a feasible, low-cost strategy for primary and secondary prevention of ankle injuries in basketball without compromising performance, and may support broader participation goals aligned with Sport for All principles. Full article

Cultural tourism (CT) has emerged as a critical driver of destination competitiveness; however, stakeholders struggle to balance heritage preservation, sustainable growth, and visitor management. Current decision making often lacks the practical information required to assess the multi-dimensional impacts of CT and to align strategies with sustainability goals. This paper presents a user-centred digital decision support system (DSS) developed under the European project IMPACTOUR. The methodological contribution is a procedure that uncovers links among strategies, actions, and performance indicators, conditioned on destination characteristics, by leveraging hierarchical multi-criteria analysis to weight sustainability domains. Co-designed with stakeholders, it integrates social and technological components and uses triangulated data to prioritise strategies and evaluate impacts. The visual interface offers a smart dashboard that supports strategic decision making and displays related key performance indicators, enabling stakeholders to monitor outcomes against predefined sustainability objectives. Pilot implementations in several European regions demonstrate the tool’s efficacy in fostering data-driven planning to achieve a balanced approach between tourism and liveability. While the system is scalable, its current limits include regional specificity and data availability. Future work will incorporate AI-driven predictive analytics and adapt the DSS for application in non-European contexts, providing a replicable framework for advancing sustainable tourism policies in culturally rich destinations. Full article

In the context of the European Green Deal and the New European Bauhaus, circularity and sustainability have emerged as central paradigms for rethinking development models in both urban and rural areas. While most literature focuses on cities, rural villages are increasingly recognised as living laboratories where cultural heritage, landscape values, and community-based practices can support sustainable and responsible tourism. This study applies the Circular Development framework to 54 European case studies of rural regeneration, examining the interrelations among cultural heritage enhancement, sustainable tourism, circular resource management, and community engagement. Through a mixed-methods approach combining frequency and cluster analysis, the research identifies strategic domains and recurring configurations of actions, contributing to the definition of a conceptual model for the Circular Rural Village. Three pillars (Circular Tourism, Circular Land, and Circular Living) articulate how cultural identity, experiential tourism, ecological regeneration, and participatory governance can foster integrated and sustainable development. The findings offer insights for policy-makers and practitioners aiming to activate regenerative tourism and heritage-led circular transitions aligned with sustainability goals. Full article

Background/Objectives: Human papillomavirus (HPV) is a major cause of cervical, penile, anal, and oropharyngeal cancers. HPV vaccination is the most effective public health strategy for its prevention. Understanding the factors influencing vaccination intentions is critical for developing effective public health policies and improving population-level vaccine uptake. Therefore, in this scoping review, we aimed to examine HPV vaccination research conducted in Korea, identify common trends and gaps in study populations and influencing factors, and provide evidence-based recommendations for public health policies. Methods: We systematically searched four Korean databases—Research Information Sharing Service (RISS), DBpia, Korean Studies Information Service System (KISS), and National Digital Science Library (NDSL)—for studies published from their respective inception dates to January 2025, using “human papillomavirus,” “HPV,” “vaccination,” and “intention” as keywords. Thirty-six studies were ultimately included. Study characteristics, populations, theoretical frameworks, and key variables were extracted and analyzed using descriptive statistics and content analysis. Results: Of the included studies, 61.1% and 38.9% targeted vaccination-eligible individuals (adolescents and adults) and parents/guardians, respectively, with 50% focusing exclusively on women. The major factors influencing HPV vaccination intention were attitude (47.2%), subjective norms (38.9%), and perceived behavioral control (30.9%). Attitude and knowledge were critical for vaccination-eligible individuals (Direct group), whereas subjective norms were key for parents/guardians (Indirect group). Conclusions: Korean HPV vaccination intention research has predominantly focused on women and parents, with insufficient attention to adolescents and men. Public health strategies must employ multilevel interventions tailored to each group’s decision-making structures, including school-based programs for adolescents, gender-inclusive policies for men, and community-based approaches to address social norms among parents. These findings provide evidence for policy development aligned with the WHO cervical cancer elimination goals. Full article

The international literature shows significant growth in relation to sustainable rural development in response to ongoing problems. The Principles for Responsible Investment in Agriculture and Food Systems (CFS-RAI) enable projects to be aligned with the Sustainable Development Goals (SDGs). In this article, we present an empirically grounded analysis of these RAI principles based on in-depth case studies in seven countries (Spain, Ecuador, Peru, Dominican Republic, Bolivia, Colombia, and Mexico). This experience comes from an international project coordinated by the GESPLAN Research Group at the Polytechnic University of Madrid. The Working with People model is incorporated into the methodological process to analyze rural actors’ understanding of the CFS-RAI principles in different countries and in university–business relation contexts. The results show the effectiveness of the WWP model based on the integration of three dimensions—ethical–social, technical–business, and political–contextual—as an effective method for planning sustainable rural development projects in various contexts. The empirical evidence presented indicates that combining the WWP model with the principles of CFS-RAI in rural contexts allows progress toward sustainable development, balancing economic aspects with human, social, and environmental well-being. Full article