Search Results (22,263)

Background/Objectives: There is a limited body of research on evidence-based food literacy education for adolescents. The inquiry-based curriculum, Teens CAN: Comprehensive Food Literacy in Cooking, Agriculture, and Nutrition, was designed to improve food literacy among adolescents ages 14–18 years. This study aimed to assess the Teens CAN curriculum by examining changes in food literacy outcomes among high school–aged adolescents and explore the effectiveness of undergraduate facilitators in implementing the curriculum with fidelity. Methods: This quasi-experimental pilot study was conducted among high school students comprising intervention (n =14) and comparison groups (n = 16). All Teens CAN lessons were delivered by trained undergraduate facilitators, and lesson fidelity was measured by a trained observer. Baseline and follow-up survey measures assessed various components of food literacy, including adolescent nutrition knowledge, diet quality, and intrinsic motivation to prepare healthy food (cooking self-efficacy). Between-group differences were examined using t-tests, and ANCOVA regression models assessed associations between changes in baseline to follow-up nutrition knowledge, diet quality, and cooking self-efficacy, adjusting for baseline values. Results: The adolescents in the intervention group had a significant increase in nutrition knowledge scores compared to the comparison group (4.6 ± 2.3 vs. 1.1 ± 3.7, respectively; p = 0.01). High fidelity (≥80%) was achieved across lessons and lesson components. In ANCOVA regression analyses, participation in the intervention was positively associated with nutrition knowledge (β = 3.3, 95% CI [0.87–5.80]; p = 0.01), providing evidence for future investigation. Conclusions: The findings from this pilot study suggest that Teens CAN has the potential to positively influence food literacy and related behaviors among adolescents, therefore warranting further investigation in a larger population. Full article

A recently proposed tensor–scalar extension of gravity coupled to extended Aharonov–Bohm electrodynamics admits one-variable traveling reductions in which a longitudinal electromagnetic scalar mode $S={\partial }_{\mu }{A}^{\mu }$ couples nonlinearly to gravitational scalars. In the weak-field regime outside sources, a one-dimensional traveling ansatz depending on $\xi =x-vt$ reduces the field equations to a coupled autonomous ODE system. The mathematical core of the reduction is a singular Newton-type equation whose classical mechanics counterpart is known; the novelty here lies in its derivation from the scalar–tensor/Aharonov–Bohm field system, in the physically motivated normalization of the traveling-wave families, and in the resulting phase–space interpretation for source-generated pulse selection. We provide a systematic classification of all admissible initial data and of the corresponding maximal solutions, distinguishing repulsive/attractive regimes and subcritical/critical/supercritical behaviors through a normalized parameter map. In particular, attractive branches may reach the singularity in finite time with a universal collision exponent $2/3$, while escaping branches exhibit asymptotically uniform motion with a computable logarithmic correction. Finally, we construct a numerical atlas of representative trajectories and validate the computations by cross-checking direct time integration against numerical inversion of the implicit quadrature, together with energy-defect diagnostics. Full article

Growing mobility demand and declining vehicle utilization motivate dual-use vehicles that can alternately transport passengers and freight. This work presents an early-stage utility value analysis to select a baseline concept and integrates it into model-based systems-engineering architecture development of an autonomous dual-use shuttle. Existing dual-use-capable shuttle concepts were screened and comparatively assessed using a utility value analysis with exclusion criteria and weighted evaluation criteria, including operational versatility, module exchange flexibility, infrastructure effort, battery positioning, and technology readiness. Criterion weights were derived by pairwise preference analysis, emphasizing the versatility of use scenarios. The highest-ranking concept, 101 Modular Mobility, was selected as the reference architecture. Subsequently, a SysML system model was developed in a MagicGrid-structured model-based systems-engineering (MBSE) process, covering stakeholder needs, key use cases such as transport service usage, module exchange, and automated charging, and the resulting system context and interfaces. The system model is augmented by a tailored Grey Box structural viewpoint within the MagicGrid workflow to make module boundaries and inter-module interfaces explicit for the modular dual-use shuttle architecture. The resulting model provides a traceable early architectural baseline for further refinement and subsequent verification activities. Full article

Neuropsychiatric disorders are characterized by complex etiologies, widespread involvement of brain regions, and pronounced clinical heterogeneity, with core pathological mechanisms closely associated with abnormal activity in deep brain structures and their functional networks. Although current pharmacological therapies and conventional neuromodulation techniques have shown therapeutic benefits in certain conditions, they are generally limited by insufficient stimulation depth or the risks associated with invasive procedures. Temporal interference (TI) electrical stimulation has recently emerged as a non-invasive deep neuromodulation technique that generates low-frequency difference-envelope fields through high-frequency carrier signals, thereby enabling relatively precise modulation of deep brain regions while maintaining favorable safety and tolerability. This technique provides a novel technical pathway for precision intervention in neuropsychiatric disorders. In this review, we summarize the principles and technical characteristics of TI stimulation and highlight its recent applications in mood and stress-related disorders, cognitive impairment and neurodegenerative diseases, movement disorders, addiction, and disorders associated with dysregulated neural excitability. We integrate its potential mechanisms across multiple levels, including neural oscillations, deep–cortical network synchronization, reward and motivational circuits, synaptic plasticity and structural remodeling, excitatory-inhibitory balance, and gene and epigenetic regulation. Current evidence suggests that TI stimulation can modulate electrophysiological activity and may engage molecular and network-level processes relevant to functional improvement, although durable clinical benefits remain to be established. Although clinical translation remains challenged by parameter optimization, interindividual variability, and long-term safety evaluation, advances in computational modeling, multimodal neuroimaging, and closed-loop stimulation strategies are expected to facilitate its development. Overall, TI stimulation represents a promising non-invasive deep neuromodulation approach for mechanistic investigation and precision treatment of neuropsychiatric disorders. Full article

This study investigates how Chinese learners of English express manners of motion, examining systematic features, cognitive motivations, and compensatory strategies. While Talmy’s motion events typology and Levin’s verb classification system provide important foundations, both have limitations in capturing the internal semantic granularity of manner verbs and the complexity of learner acquisition. To address this, we construct a 10-level verb typology establishing a “semantic granularity” continuum from concrete to abstract, physical to metaphorical, and lexical to grammatical. Using experimental data (N = 600) and corpus comparisons (COCA vs. learner corpus), we analyze Chinese learners’ manner expression patterns. Results reveal the following: (1) Chinese learners prioritize Path over Manner, overusing lower-level verbs (go, walk, run) while underusing higher-level and fine-grained manner verbs (stroll, scramble), which are preferred by native speakers. (2) Learners favor semi-tight or loose syntactic structures and show a preference for describing Manner precisely by adding other modifiers such as adverbials, prepositions, complements, or subordinate clauses. When it comes to precisely describing specific manners of motion, Chinese learners of English tend to use four strategies—analytic manner externalization, path salience, image-schematic transfer, and semantic simplification—whereas native English speakers typically rely on single verbs with high semantic density. These findings suggest learners’ expression of manner involves both L1 syntactic transfer and target language conceptual adaptation. The 10-level classification continuum advances the theoretical understanding of motion event lexicalization patterns, provides new perspectives for conceptual transfer research, and offer pedagogical implications for Chinese English learners’ accuracy of their expression of manner. Full article

Malnutrition—including undernutrition, micronutrient deficiencies and overweight—remains a major public health concern in sub-Saharan Africa, largely driven by food insecurity. Edible insects have been proposed as a sustainable, nutrient-dense dietary alternative with potential to improve food security and nutritional outcomes. This review analyses studies published until January 2024 in PubMed and Google Scholar assessing the prevalence, acceptability and nutritional impact of insect-based diets in sub-Saharan Africa. Thirteen original studies, predominantly qualitative, conducted in 8 of 47 countries in the region, met inclusion criteria. Two reviews provided additional evidence. Most studies focused on acceptability, which was strongly influenced by cultural and religious norms. Higher acceptance was observed among older individuals and those with lower educational attainment, while younger and more urbanized populations showed greater reluctance. Reported motivations for consumption included tradition, taste and perceived nutritional value. Some studies highlighted potential health risks related to food safety and the need for improved regulatory frameworks. The available nutritional analyses showed that edible insects are rich in protein and essential micronutrients, particularly iron and zinc, suggesting their potential to address common deficiencies. Although evidence on long-term nutritional impact remains limited, current findings support the feasibility and potential public health relevance of promoting insect-based diets in low-income settings. Full article

Background: Ultraviolet (UV) radiation is a major risk factor for skin cancer. Nevertheless, many people tan in the sun and in tanning beds. The aim of this study was to explore the reasons behind these behaviors and to investigate whether the reasons for tanning in the sun and in tanning beds differ. Methods: We used data from a nationwide survey study conducted in Germany, which included n = 4156 individuals aged 16 to 65 years. We assessed different reasons for outdoor and indoor tanning, as well as sociodemographic characteristics, skin type, and tanning behaviors. Results: While both outdoor and indoor tanners frequently reported relaxation, as well as feeling of light and warmth as reasons, outdoor tanners placed a greater emphasis on increasing vitamin D levels and health benefits. In contrast, indoor tanners were more focused on enhancing attractiveness and pre-tanning for holidays. Individuals who sought a tan more frequently—whether through indoor or outdoor tanning—were more likely to agree with the various reasons provided, compared to those who tanned less often. In addition, we found associations with sex, age, immigrant background, education, occupation, and skin type. Conclusions: There were differences as well as similarities in the reasons for indoor and outdoor tanning. This indicates that overarching prevention strategies could be effective. Additionally, targeted measures specifically for indoor and outdoor tanning could also be beneficial in raising awareness about the risks of UV radiation and, in the long term, reducing the incidence of skin cancer. Full article

Self-healing materials (SHMs) are a class of bio-inspired materials capable of autonomously repairing damage, similar to how living organisms heal wounds. The core motivation behind SHMs is to extend the service life of components while enhancing safety and reducing maintenance or replacement needs. SHMs can be broadly categorized into intrinsic systems, which rely on reversible internal bonds (dynamic covalent or supramolecular interactions) to heal repeatedly, and extrinsic systems, which embed external healing agents (e.g., microcapsules or vascular networks) that are released upon damage to effect repairs. Researchers have demonstrated self-healing behavior in diverse material families, including polymers, metals, ceramics/cementitious materials, and protective coatings, thereby improving crack resistance, fatigue life, and reliability across aerospace, automotive, civil infrastructure, energy storage, and microelectronics applications. Advances in material design and additive manufacturing have started integrating SHMs into practical structures. However, challenges such as scaling up production, maintaining mechanical performance, and ensuring long-term durability remain. Reported healing efficiencies in self-healing materials typically range from ~50% to near-complete recovery (~100%), depending on material systems and testing conditions, highlighting key trade-offs between healing performance, mechanical integrity, and scalability. Overall, SHMs represent a promising strategy for creating safer and more sustainable engineering systems, with ongoing developments aimed at overcoming current limitations and expanding their capabilities. This review highlights key trade-offs between healing efficiency, mechanical performance, and scalability, providing insights into the design and application of next-generation self-healing materials. Full article

Surface protection and functional modification of aircraft-certified aluminum alloys are essential for corrosion resistance, durability, and long-term airworthiness. At the same time, increasingly restrictive environmental regulations motivate the development of alternatives to legacy wet-chemical surface treatments. This study presents an integrated assessment of ultrafast femtosecond laser surface texturing as a surface functionalization approach for Aluminum 6061 alloys within an aerospace manufacturing and sustainability context. Ultrashort-pulse laser processing enables controlled micro- and nano-scale surface topographical modification with limited thermal impact, allowing adjustment of wettability and surface functionality while preserving bulk material integrity. As a dry and contactless process, femtosecond laser treatment eliminates the use of hazardous chemicals, reduces consumable inputs, and generates minimal secondary waste. A streamlined cradle-to-gate life cycle assessment conducted in accordance with ISO 14040/14044 indicates a lower global-warming potential per functional unit compared with conventional surface treatments, including anodization, plasma-assisted coatings, and organic coating systems. Complementary qualitative analyses addressing environmental health and safety, supply-chain risk, and ESG alignment indicate potential advantages related to occupational safety, regulatory compliance, waste management, and end-of-life recyclability. The investigation is performed on planar Aluminum 6061 reference surfaces with a treated area of 25 mm², providing a controlled laboratory-scale basis for analyzing process behavior, functional surface modification, and associated environmental metrics. Within this defined scope, the results support further evaluation of femtosecond laser surface texturing as a surface engineering option for future aerospace manufacturing. Full article

For battery management systems, accurate remaining useful life (RUL) prediction is important, yet models trained offline may not remain well matched to individual cells during operation, because degradation trajectories differ across cells and evolve over aging stages. This study examines a lightweight online personalization strategy under a representative convolutional neural network–long short-term memory (CNN–LSTM) online-transfer setting while keeping the backbone architecture and fixed input length unchanged. The proposed method restricts online updates to a small adaptation path and adjusts the effective history span according to recent degradation behavior. Experiments on 22 test cells under unseen protocols show that the method improves average post-adaptation RUL performance relative to the representative baseline, reducing the root mean square error (RMSE) from 186.00 to 160.58. The number of trainable parameters involved in online updating is reduced from 74,880 to 2193, while the average update time per step decreases slightly from 2.54 s to 2.29 s. Cell-level analysis further shows that the benefit is not uniform across all cells, motivating more selective updating for safer deployment. Overall, the results indicate that lightweight online personalization can improve the accuracy–cost trade-off of deployment-oriented battery prognostics. Full article

Safety-oriented UAV motion planning relies on distance-to-obstacle fields and their gradients, yet onboard mapping is typically limited to bounded local distance updates. Consequently, optimization may stall outside the updated band due to missing gradients, while enlarging the update range substantially increases computational cost. Our key insight is that motion-planning locality implies only a small subset of obstacles governs local trajectory refinement. We term this subset points of interest (POIs). Motivated by this observation, we develop a locality-aware sequential motion planning framework with a POI-driven feedback mechanism that continuously identifies and augments these trajectory-relevant obstacles during search and optimization. The mechanism tightly couples mapping, search, and optimization and enables safe trajectory refinement without requiring global distance updates. The framework adopts a heuristic mapping strategy that combines a long-term occupancy grid with bounded incremental distance updates and a POI-based short-term k-d tree, enabling efficient nearest-neighbor queries and gradient proxies beyond the update band. The search process generates a dynamically feasible initial trajectory in the long-term map while collecting POIs, which are then used to construct the short-term component. The trajectory is subsequently refined through iterative optimization loops, where newly exposed closest obstacles are incorporated into the POI set and the short-term map is updated until convergence. Safety is enforced through conservative collision checking against the inflated long-term occupancy map. Simulations in building and forest environments show that 99.7% of trials converge within two refinements in sparse scenes and none exceed four overall. Compared with FastPlanner and EgoPlanner, the proposed method achieves consistently larger obstacle clearances. Onboard experiments further validate its practicality under real sensing and computational constraints. Full article

Although the standard cosmological model successfully describes most current observational data, it faces several theoretical and observational challenges that motivate the exploration of alternative frameworks. In this work, we investigate a class of geometric cosmology models (GC) obtained by adding an infinite tower of higher-order curvature invariants to the Einstein–Hilbert action. Focusing on an exponential ansatz for the characteristic function entering the modified Friedmann equations, we derive the late-time background evolution for three families of solutions within this framework, named as (i) GILA, (ii) GR-deformation, and (iii) non-GR contribution. These models are confronted with recent Cosmic Chronometer and Type Ia supernova data, as well as age estimates of the oldest globular clusters—a constraint frequently overlooked in the literature. The stiffness of the equations in certain regions of parameter space, together with technical difficulties arising from the inclusion of the globular cluster bound, motivates the development of a dedicated methodology as an alternative to standard Markov Chain Monte Carlo techniques. Our results show that two entire families of GC models (non-GR contribution and GR-deformation) are ruled out by the data, whereas some families within the GILA model can successfully account for all data sets. For these models, meaningful constraints on their free parameters can be derived from the statistical analysis. Nevertheless, model comparison criteria reveal a preference in the data for $\Lambda$CDM over the GILA models examined here. Although none of the proposed models provides a preferred alternative to $\Lambda$CDM given the specific characteristic function considered here, this work establishes a clear methodology for testing alternative cosmological models, including the globular cluster constraint, and indicates the way for future research of GILA models with alternative choices of the characteristic function. Full article

Class II biological safety cabinets (BSCs) are designed to protect the user, the product, and the laboratory environment by maintaining HEPA-filtered airflow; however, their fans, alarms, and structural resonances introduce acoustic and vibrational stimuli that may confound mechanosensitive cell-culture assays. In this study, we characterized the vibroacoustic environment of a cell-culture laboratory and a Class II BSC, selected representative tray locations based on measured and modeled stimuli, and evaluated in vitro wound closure in HaCaT keratinocytes using a scratch assay under alarm-induced acoustic exposure. Wound closure after 24 h was quantified using a relative area-closure metric defined as one minus the ratio of wound area at 24 h to wound area at 0 h. For each biological replicate (one flask and one scratch), two non-overlapping image regions were treated as technical subsamples and averaged to obtain a single flask-level value. Three independent experimental runs were performed, each including one flask per tray point, yielding n equals 3 independent flasks per tray point. Mean wound closure values were 73.7 percent plus or minus 15.6 percent, 75.6 percent plus or minus 7.2 percent, and 79.4 percent plus or minus 14.8 percent for tray points P1, P5, and P6, respectively (mean plus or minus standard deviation). No statistically significant differences were detected among points (one-way ANOVA on flask-level values, F equals 0.15, p equals 0.86). These findings highlight that BSC-associated acoustic and vibration stimuli should be documented when interpreting scratch-assay outcomes and motivate larger, sham-controlled studies to resolve small effect sizes relevant for assay reproducibility. Full article

Generative AI systems trained on synthetic data exhibit progressive degradation known as model collapse. This paper provides a theoretical explanation of this phenomenon using Shannon’s Data Processing Inequality (DPI), modeling iterative synthetic-data training as a Markov chain of lossy transformations. We show that mutual information with respect to the original data distribution must decrease monotonically, yielding qualitative predictions for exponential decay tendencies and indicating that information loss arises from general finite-precision and capacity constraints rather than from any specific architectural mechanism. Building on this analysis, we introduce the AI conceptual theorem, a generalized stability limit for computable systems. The theorem states that any purely computational system that generates outputs iteratively under finite precision, bounded capacity, and without external low-entropy input must experience cumulative information degradation after a finite number of steps. DPI-based collapse emerges as a special case of this broader principle. The framework is intended as a conceptual information-theoretic perspective rather than a fully formalized theory, with several assumptions intentionally simplified to highlight the underlying entropic mechanism. The results should therefore be interpreted as principled limits that motivate further empirical and mathematical investigation rather than as definitive closed-form predictions. Together, DPI and the AI Theorem provide a unified information-theoretic framework for understanding degradation in synthetic training, long-horizon inference, and other iterative computational processes. The resulting predictions are quantitatively falsifiable and offer guidance for designing more stable and information-preserving AI systems. Full article

This study developed and validated a specialised emotional intelligence (EI) scale for youth in the conflict-affected southern border provinces of Thailand. The primary objective was to establish a psychometric instrument tailored to this unique multicultural and sensitive context. Utilizing a sample of 500 local youth leaders, the instrument’s quality was rigorously evaluated through Second-order Confirmatory Factor Analysis (CFA) using Maximum Likelihood estimation. The final validated model comprises 25 indicators categorized into five dimensions: Self-Awareness, Self-Regulation, Self-Motivation, Social Awareness/Empathy, and Relationship Management. Results indicated an excellent model fit with empirical data (χ² = 284.15, df = 265, p = 0.198, CFI = 0.99, GFI = 0.97, RMSEA = 0.02). Factor loadings ranged from 0.72 to 0.92, while composite reliability (CR) and average variance extracted (AVE) values exceeded 0.88 and 0.61, respectively, confirming high internal consistency and construct validity. Social Awareness/Empathy emerged as the most significant dimension (B = 0.91). This study suggests that the scale is a robust tool for assessing EI in conflict zones, providing a critical foundation for targeted psychosocial interventions and sustainable peace-building initiatives among youth in the region. Full article