Search Results (2,366)

Background/Objectives: Emerging evidence shows that dual tasking as well as the restriction of arm movements independently lead to detrimental effects on walking performance. However, it is unclear whether the deteriorations are more pronounced when applied together and if children (i.e., due to ongoing maturation processes) perform differently compared to young adults. This study investigated the influence of different arm movement strategies on subjective and objective markers related to beam walking under single-task (ST) and dual-task (DT) conditions in children and young adults. Methods: Twenty-six children (age: 11.3 ± 0.6 years) and 30 young adults (age: 23.2 ± 2.8 years) walked three meters on a balance beam with free and restricted (i.e., arms crossed over the chest) arm movements in a random order while concurrently performing a cognitive task (i.e., serial subtractions) or not. Walking outcomes (i.e., gait speed, cadence) were measured and used as objective markers. Self-reported task-related perceptions (i.e., balance confidence, fear of falling, perceived instability, conscious balance processing) were assessed and used as subjective indicators. Results: Walking under DT conditions (i.e., main effects of task) detrimentally influenced subjective task-related perceptions and walking outcomes, but using free arm movements (i.e., task × arm interactions) mitigated these deteriorations. Further, children exhibited largely stable levels of conscious balance processing, whereas young adults demonstrated overall higher levels along with pronounced differences between ST and DT walking when arm movements were unrestricted (i.e., group × task × arm interaction). Conclusions: These findings indicate that free arm movements seem to constitute a simple yet effective complementary ‘upper-body strategy’ that enhances postural control during a cognitively demanding walking task. Further, age differences imply that young adults compensate demanding walking conditions (i.e., DT walking with restricted arms) by elevated conscious processing of balance (i.e., a shift from automated to more conscious attention towards postural control). Full article

Achieving sustainable design requires balancing environmental performance, resource efficiency, functional feasibility, and aesthetic acceptance throughout the product life cycle. However, traditional design approaches often struggle to quantitatively integrate subjective aesthetic evaluation with objective sustainability indicators such as energy consumption, carbon emissions, and material recyclability. To address this challenge, this study proposes a semantic-guided multi-objective optimization framework for sustainable design that integrates cross-modal aesthetic evaluation with life cycle environmental performance assessment. The proposed framework employs a Contrastive Language–Image Pre-training (CLIP)-based semantic evaluation mechanism to translate abstract sustainability and aesthetic concepts into quantifiable design features, enabling consistent assessment across diverse design solutions. These semantic features are further optimized using a multi-objective evolutionary optimization strategy to simultaneously minimize energy consumption and carbon emissions while maximizing material recovery and design quality. Life cycle environmental indicators derived from OpenLCA datasets are incorporated into the optimization process to ensure practical sustainability relevance. The experimental results demonstrate that the proposed framework achieves a superior performance compared with benchmark optimization methods. Specifically, carbon emission equivalents are reduced to as low as 12.3 kg CO₂e, material recovery rates exceed 92%, and total computational energy consumption is reduced by more than 40% relative to comparative models. In addition, the framework shows strong stability and convergence efficiency while maintaining a high aesthetic evaluation accuracy in high-quality design ranges. The findings indicate that the proposed approach provides an effective pathway for integrating aesthetic value with environmental responsibility in sustainable design practice. This framework supports low-carbon and resource-efficient product development and offers practical insights for sustainable manufacturing, circular design, and environmentally conscious innovation. Full article

Generative AI (GenAI) is transforming higher education assessments, yet empirical research on students’ lived experiences with GenAI during graded, time-constrained classroom assessments remains scarce. This study investigates how direct experience with GenAI in examinations shapes student perceptions of learning, metacognition, and engagement. Drawing on self-regulated learning research and cognitive load theory, we employed a retrospective pre–post design to analyze qualitative reflections and quantitative data from 90 undergraduate computer science and engineering students. Our qualitative analysis suggests a complex recalibration from idealized expectations of efficiency toward what may be described as a state of measured pragmatism. Interpretive analysis of Post-experience reflections indicates that direct practical engagement appeared to make students more conscious of the need for metacognitive engagement, with a focus on real-time output verification and the restrictive role of time pressure. Concerns regarding assessment authenticity and fairness emerged only after direct engagement. Quantitative results show that although 68.5% preferred the GenAI format, this preference did not correlate significantly with academic performance (r = 0.014, p = 0.89). Those findings suggest that student engagement is driven by pedagogical and professional relevance rather than grade improvement alone. Overall, the findings underscore the need for assessment designs that balance cognitive support with active student monitoring and responsibility. Full article

In recent years, Visual Education has emerged as an innovative and interdisciplinary teaching approach aimed at promoting meaningful learning through the conscious use of visual tools and languages. This educational paradigm helps to facilitate the understanding of complex concepts, translating them into clear and intuitive visual representations, while enhancing memorisation skills, critical information processing and the practical application of acquired knowledge. This systematic review, conducted according to the PRISMA (2020) protocol, analyses the most recent empirical evidence on the effectiveness of Visual Education in educational contexts. The main objective is to assess how the intentional use of visual tools—images, concept maps, educational videos, interactive digital materials, and virtual manipulatives—contributes to enhancing learning processes and developing transversal skills. Through a comparative analysis of fourteen international contributions published between 2020 and 2025, selected from the Scopus, Web of Science and EBSCO databases, the research highlights how Visual Education significantly influences the improvement of academic performance, motivation and cognitive and emotional engagement of students. The results also confirm the inclusive function of visual teaching, which can encourage participation, self-esteem and cooperation even in individuals with special educational needs. The discussion emphasises the need for the systematic integration of Visual Education into school curricula as a strategy to enhance soft skills and promote more equitable, effective learning geared towards the integral development of the individual. Full article

This study falls within the field of lifelong education and investigates the role of aesthetic-sensory experiences—particularly those mediated by digital visual arts—in the development of critical thinking, a key competence identified in the European LifeComp Framework. In light of contemporary social transformations characterised by complexity, uncertainty, and change, critical thinking emerges as a transversal skill of fundamental importance for the education of conscious and autonomous citizens. The objective of this research is to analyse how digital sensory experiences, integrated with innovative teaching methodologies—such as laboratory-based teaching and collaborative learning—can foster the activation and enhancement of critical thinking in educational contexts. The work is based on a narrative analysis of the literature, conducted through the consultation of academic databases (e.g., Scopus, ERIC, and Google Scholar), and is developed within a theoretical framework encompassing digital education, laboratory didactics, and collaborative learning strategies. Studies published in recent years were selected according to their relevance to digital aesthetic experiences and critical thinking in educational contexts and were analysed through a thematic synthesis of the main conceptual contributions. The knowledge activities include the selection, categorisation, and discussion of recent studies that relate aesthetic experiences to the development of soft skills, in line with the principles of visual education understood as aesthetic and critical literacy in visual languages. The results of the review indicate that the intentional use of aesthetic digital environments, in combination with active and reflective teaching approaches, can stimulate complex cognitive processes and significantly contribute to the formation of critical thinking. The contribution implements an interdisciplinary approach among visual education, digital education, and experiential aesthetics, emphasising the need for further empirical research to consolidate the evidence and guide the implementation of innovative educational practices based on this approach. Full article

Background: n-3 Docosapentaenoic acid (DPA; 22:5 n-3) is increasingly viewed as a distinct long-chain omega-3 fatty acid with biological activities that are not fully captured by eicosapentaenoic acid (EPA) or docosahexaenoic acid (DHA). However, progress remains limited by restricted access to high-purity DPA: most commercial sources contain DPA as a minor component, and published isolation strategies often yield only enriched mixtures or require multi-step workflows that are difficult to scale in standard laboratories. Objectives: We aimed to establish a robust, laboratory-accessible purification workflow to obtain DPA ethyl ester at high purity while preserving oxidative quality. Methods: Candidate lipid sources were screened to select an optimal DPA-containing feedstock. Oils were stabilized with antioxidants and pre-fractionated by cold crystallization (−20 °C) to reduce saturated lipids and oxidation by-products. Preparative separation used a stacked C18 flash system (15 μm + 45 μm in series) operated isocratically (methanol/water 92:8, v/v) at 120 mL/min. Fractions were analyzed by GC and iteratively reinjected to progressively enrich the DPA window. Solvent was recovered by distillation and reused. Results: Omegavie^® 4020EE (5.4% n-3 DPA) was identified as the best starting material. Pretreatment eliminated detectable TBARS-derived malondialdehyde. The isocratic purification-loop strategy produced tens of grams of DPA ethyl ester at >98% purity (GC–FID) defined as n-3 DPA area% of total identified fatty acid methyl esters by GC–FID, with per-cycle DPA recovery of 91–95%, overall recovery of 76% from the starting DPA content, and >90% solvent recycling. The workflow is scalable at the gram-to-tens-of-grams level for research laboratories, although solvent burden and column maintenance remain practical constraints for larger-scale implementation. Identity and purity were confirmed by GC–MS and ^1H NMR, and oxidation indices remained low (peroxide value < 0.2 meq/kg; p-anisidine < 3). Conclusions: This scalable, solvent-conscious protocol enables reliable access to high-purity DPA and should be adaptable to other low-abundance polyunsaturated fatty acids. Full article

Blade Tip Timing (BTT) provides a superior long-term blade monitoring solution compared to strain gauges, yet its adoption in lower value turbomachinery remains constrained by sensor costs. This study explores Inductive Proximity (IP) probes as a cost-effective alternative to eddy current probes. Experimental results demonstrate that the IP probes achieve comparable accuracy in natural frequency estimation while being 40 times more affordable than traditional active eddy current probes. Additionally, IP probes maintain robustness, ensuring reliable vibration parameter extraction via open-source BTT software (version 0.17.0). These findings significantly enhance the accessibility of BTT, enabling budget-conscious turbomachine manufacturers to implement high-precision blade monitoring solutions across a wider range of applications. Full article

Locked-in Syndrome (LIS) is a neurological condition in which individuals remain conscious but experience complete paralysis of voluntary muscles, except for eye movements—highlighting the need for reliable assistive communication technologies. This study presents the design and evaluation of an Arabic electrooculogram (EOG)-based communication system with adaptive classification capabilities for LIS applications. A custom-designed EOG acquisition circuit incorporating filtering and amplification stages was implemented and compared with the OpenBCI Cyton board. The system employed a hybrid classification approach combining amplitude, temporal, and statistical features to distinguish between blinks and voluntary vertical eye movements. Testing with ten healthy subjects yielded a mean classification accuracy of 83.96% ± 4.59% and an information transfer rate of 10.43 letters per minute, corresponding to a 30.38% improvement over conventional approaches. The custom-designed circuit achieved a signal-to-noise ratio of 25.21 dB, outperforming the OpenBCI Cyton board by 8% while reducing system cost by 62%. The integration with a Morse code-based interface enabled Arabic letter composition, while the system incorporated auto-completion and text-to-speech functionalities to further enhance communication efficiency. This cost-effective solution addresses a critical gap in assistive technologies for Arabic-speaking individuals with LIS and shows strong potential for enhancing their communication abilities and overall quality of life. Full article

Heavy metals including mercury (Hg), lead (Pb), cadmium (Cd), and arsenic (As) remain significant global toxins due to their environmental persistence, widespread anthropogenic release, and serious biological effects. This review consolidates current understanding of their natural and industrial sources, environmental cycling, human exposure routes, and population-level vulnerabilities. It covers their toxicokinetics and toxicodynamics, emphasizing species-specific absorption, distribution, and injury mechanisms, including oxidative stress, thiol binding, mitochondrial dysfunction, endocrine disruption, and cancer risk. Clinical signs range from subtle neurocognitive impairment and kidney damage to severe acute poisoning. The review evaluates evidence-based approaches to risk assessment and biomonitoring, such as blood, urine, hair, and speciation tests, noting issues, including unvalidated provoked testing. Treatment focuses on removing exposure, providing nutritional support, and offering supportive care, with chelation therapy reserved for specific cases. It explains the chemistry, pharmacology, and roles of chelating agents—ALA, DMSA, DMPS, Cys, GSH, and physiologic thiols, comparing their effectiveness, limitations, and costs for various metals. Emerging therapies, precision toxicology, and public health strategies are discussed within a prevention-focused context. Unlike prior reviews focused primarily on toxic mechanisms or isolated clinical management, this review integrates mechanistic toxicology, biomarker interpretation and speciation, evidence-based clinical care, and ethical, cost-conscious decision-making within a single translational framework. This narrative review synthesizes foundational and contemporary literature published through 2025, with particular emphasis on studies published since 2000 that inform toxicokinetics, biomarker interpretation, diagnostics, clinical management, and prevention. Full article

Activewear has become a common component of women’s everyday clothing, yet emerging evidence suggests that exposure to activewear imagery may adversely affect body image. This study aimed to describe women’s activewear engagement across contexts and to investigate how different markers of engagement correspond with positive outcomes such as fitness behavior, body appreciation, and self-esteem, as well as negative outcomes including media pressure, idealized appearance aspirations, and self-objectification. We collected survey data from student (N = 455) and community (N = 37) samples to assess activewear-related behaviors, including online browsing, social media following, purchasing, and wearing, as well as measures of fitness behaviors, body appreciation, self-esteem, idealized body aspirations, appearance comparisons, perceived media pressure, and self-objectification. Across samples, 40–87% of women engaged with activewear in some form, and 30% reported feeling self-conscious at least half the time they wore it; notably, activewear was worn for exercise less than 50% of the time. Activewear engagement showed positive correlations with fitness behaviors but also with idealized body aspirations, appearance comparisons, media pressure, and self-objectification, while showing no associations with body appreciation or self-esteem. These findings highlight the growing cultural prominence of activewear and suggest that engagement with this clothing trend is linked to both adaptive and risk-related psychological factors, underscoring the need for further research into its broader psychological implications. Full article

Phytochemicals have attracted considerable attention as therapeutically relevant bioactive compounds due to their diverse pharmacological activities, including anti-inflammatory, antioxidant, anticancer, and metabolic regulatory effects. However, their clinical translation is frequently hindered by unfavorable pharmaceutical properties such as poor aqueous solubility, chemical instability, rapid metabolism, and limited bioavailability. These challenges have constrained the reproducibility and therapeutic reliability of phytochemical-based interventions. In this context, nanotechnology-enabled delivery systems have emerged as effective strategies to overcome the intrinsic limitations of phytochemicals and enhance their biological performance. This review provides a comprehensive overview of recent advances in nanotechnology-based delivery platforms for phytochemicals, with emphasis on lipid-based nanocarriers, polymeric nanoparticles, nanoemulsions and self-nanoemulsifying drug delivery systems, inorganic and hybrid nanocarriers, as well as hydrogel-based and transdermal delivery systems. We discuss how rational nanocarrier design improves solubility, stability, pharmacokinetics, cellular uptake, and tissue targeting, thereby enhancing therapeutic efficacy across multiple disease areas. In addition, critical safety, toxicity, manufacturing, and regulatory considerations that influence translational potential are addressed. By adopting a delivery-centered perspective, this review highlights current challenges and future opportunities in nano-phytomedicine and underscores the importance of integrating nanotechnology, biological insight, and regulatory-conscious development to advance phytochemicals toward clinically viable therapeutic applications. Full article

The purpose of this instrumental case study, employing both qualitative and quantitative data, was to investigate how novice teachers from non-local and urban areas used community assets and local funds of knowledge (FoK) in their STEM instruction in a remote Montana town. While non-local teachers often make up a large share of many rural communities’ teaching workforce, those teachers might lack the social, cultural, and community knowledge that they need to teach with place-conscious approaches. Therefore, this study explored how “new-to-town” teachers, with limited personal ties to a community, learn about their rural community and how they apply this knowledge to their teaching context. Additionally, this study examined which research-established factors that improve rural STEM education were deemed most important for novice, rural teachers. The exploration employed a floodlight research approach, whereby a census of the authentic pedagogical actions of the subjects was documented rather than investigating the efficacy of a single method. Data sources included qualitative instruments like concept maps and semi-structured interviews, alongside quantitative measures like ranked best-practices data and place-conscious lesson ratios, to provide both depth of interpretation and breadth of comparison across participants. Results from the deductive thematic analysis suggest that novice teachers aspire to implement asset-based pedagogical approaches in STEM instruction and possess some methods for integration but struggle to learn of local community assets without modeling and mentorship. Additionally, an unexpected pattern emerged from the findings: Novice, newcomer teachers that employed place-conscious lessons were more likely to remain teaching in their position. While this association cannot be interpreted causally, it might suggest that place-conscious mentorship practices may play a role in improving instruction and support the retention of non-local teachers in rural communities however, further, more robust exploration is warranted of this exploratory finding. Findings from this study can be used to inform recommendations for school districts, post-secondary institutions, and rural communities on how best to support beginning rural teachers with limited community connections. Full article

Digital transformation in the interior design industry has opened new opportunities for innovation; however, many cost-conscious homeowners still face difficulties in selecting and customizing design packages that achieve a balance between overall cost and sustainable quality. Existing interior design platforms lack seamless support and often require homeowners to invest considerable time and effort to tailor services to their needs while staying within budget. To address these challenges, this paper explores the use of machine learning to build a predictive modelling framework that supports personalized and value-driven interior design recommendations. The proposed approach uses a hybrid recommendation system that combines content-based and collaborative filtering. It also incorporates lightweight techniques such as TF–IDF (Term Frequency–Inverse Document Frequency) and logistic regression to more effectively capture user preferences, budget limits, and several interior-design service categories. Primary data was collected from small to medium-sized interior design companies. To demonstrate the proposed approach, a user-friendly web application tool is developed to integrate machine learning-enabled recommendation services. The resulting solution provides access to professional interior design services, enhancing customization and customer satisfaction while reducing the time and effort required from homeowners. To validate and compare the performance of the proposed approach, several machine learning models including Random Forest, XGBoost and KNN (K-Nearest Neighbors) were tested using standard metrics such as accuracy, precision, recall, and ROC-AUC (Receiver Operating Characteristic-Area Under the Curve). The proposed logistic regression hybrid model achieved the strongest overall results, with an accuracy of 83.62%. These findings demonstrate the significant contribution of this work to enhancing personalization and accessibility in the interior design sector via machine learning-enabled recommendation systems. The proposed approach bridges the gap between expert-level services and financial limits, making it a practical choice for cost-conscious homeowners. Full article

Waste separation in private households remains difficult to promote, particularly in urban contexts, where anonymity limits informal social monitoring. This proof-of-concept study tested, for the first time, self-administration of images of “watching eyes” as an intervention. About 22% of all households living in the district of Riedberg in Frankfurt/Main, Germany, received a letter asking residents to attach eye cues to kitchen and outdoor waste bins to prompt appropriate separation of organic from residual waste. Objective data from weighed collection trucks showed a measurable behavioral effect compared to control conditions, with a 5–8% increase in biowaste volumes. While this study does not allow causal inference because waste was measured only at the group level, it does suggest that, when applied by residents themselves, social nudges might enhance self-awareness about environmentally conscious behavior. Accompanying survey responses displayed ceiling effects, presumably because only highly motivated individuals participated. Importantly, some signs of reactance were also observed, with some participants perceiving the intervention as intrusive and regulatory. Although low-cost and easy to apply, self-administration of watching-eyes cues requires careful communication and attention to psychological reactions to avoid resistance while encouraging the formation and maintenance of target habits in private environments. Full article

Recent research demonstrates that guilt, as a self-conscious moral emotion, can shape early visual perception. However, the underlying neural mechanisms remain unclear. Using a pre–post experimental design combined with electroencephalography (EEG), we investigated how guilt modulates visual size perception and its neurophysiological correlates. Across four experiments, we confirmed that guilt emotion consistently increased the size overestimation component of the Ebbinghaus illusion. Time–frequency analyses revealed that guilt processing involved decreased prefrontal theta (4 to 7 Hz) power and reduced phase coupling of prefrontal theta and temporo-parieto-occipital alpha (8 to 12 Hz) oscillations. The guilt-related modulation of visual size perception was specifically associated with occipital alpha phase coherence. These results demonstrate that guilt emotion shapes fundamental visual processing through coordinated neural oscillations across large-scale brain networks. The findings advance understanding of emotion–cognition interactions and have implications for guilt-related psychiatric disorders. Full article