Search Results (3,778)

Growing evidence indicates that executive functions, metacognition, and reading comprehension are crucial for academic success; however, their contribution to academic achievement in gifted children remains insufficiently understood. The main aim of this study was to compare planning processes and metacognitive abilities among gifted children with high academic achievement, gifted children with low academic achievement, and typically developing children with high academic achievement. A secondary aim was to examine reading comprehension in gifted children compared to typically developing peers. Seventy-three children (34 males, 39 females), aged between 8 and 11 years (M = 9.5, SD = 0.91), were divided into three groups: gifted children with high academic achievement, gifted children with low academic achievement, and typically developing children. Participants completed the Tower of London task, the MT Reading Comprehension Test, and the Me and My Mind metacognition questionnaire. Results showed that both groups of gifted children performed significantly better than typically developing peers in planning efficiency and reading comprehension. No significant differences emerged between high- and low-achieving gifted children in planning, reading comprehension, or metacognition. Overall, the findings suggest that planning abilities and reading comprehension represent cognitive strengths that distinguish gifted children from typically developing high achievers, whereas differences in academic achievement within the gifted population may be more closely related to metacognitive regulation and other non-cognitive factors rather than to planning or reading comprehension alone. Full article

Tunnel lighting cleaning is of significant practical importance for improving driving safety. To address the low operational efficiency of tunnel lighting cleaning tasks, a trajectory planning method based on the chaotic adaptive whale–particle swarm optimization (CAW-PSO) algorithm is proposed. Taking the SIASUN GCR16-2000 robotic arm as the research object, the trajectory is constructed using a 3-5-3 polynomial interpolation, with the objective of achieving time-optimal trajectory planning. In the CAW-PSO algorithm, a tent chaotic map is introduced to improve the quality of the population; a linearly decreasing inertia weight is designed to strike a balance between local and global search; dynamic learning factors are defined to strengthen the individual learning ability and global cognitive capability of particles; finally, the exploitation mechanism of the whale optimization algorithm is employed to avoid getting trapped in local optima and improve convergence accuracy. The simulation time is 3.661 s, a reduction of 69.94%. The experimental results yielded a mean relative error of 1.16%, indicating good agreement with the simulation results. The results of the simulation and experiment indicate that the CAW-PSO effectively reduces the motion time of the robotic arm, exhibiting superior applicability in trajectory planning for tunnel lighting cleaning robotic arms. Full article

Introduction: Large language models (LLMs) are increasingly employed as cognitive aids in research and professional inquiry, yet their fluent outputs are frequently regarded as authoritative knowledge. We contend that this practice signifies a fundamental epistemic misalignment. Methods/Approach: Building on Peirce’s theory of inquiry, Sellars’ concept of the space of reasons, Stanovich’s tripartite model of cognition, and knowledge-building theory, we develop a conceptual framework for analyzing epistemic agency in human–LLM collaboration. Results/Argument: We demonstrate that LLM outputs fail to satisfy the conditions for knowledge because they lack reflective regulation, resistance to revision, and normative commitment. While LLMs display strong autonomous and algorithmic abilities (e.g., pattern recognition and hypothesis development), reflective control remains a distinctly human function. This asymmetry supports a principled division of epistemic labour and motivates the concept of the Knowledge-Building Partner (KBP): an AI system designed to support inquiry without claiming epistemic authority. Discussion/Implications: We identify prompt-, system-, and model-level design requirements and introduce a triangulated framework for operationalizing epistemic agency through explainable AI, discourse analysis, and rational-thinking measures. These contributions collectively reposition LLM limitations as epistemic design challenges rather than technical issues. Full article

Background: Tetrasomy X (48, XXXX) is an extremely rare sex chromosome aneuploidy characterized by highly variable phenotypic manifestations. It includes various medical issues, a wide range of developmental delays, and neurocognitive deficits. Methods: The present case report provides a comprehensive neurodevelopmental profile of a 4.5-year-old girl with Tetrasomy X, with the aim of contributing to phenotype delineation, exploring genotype–phenotype associations, and emphasizing the importance of early, targeted intervention. A multidisciplinary assessment was conducted, encompassing cognitive, speech–language, motor, sensory, adaptive, and socioemotional functioning, using a battery of standardized and culturally adapted instruments. Results: Results revealed borderline intellectual functioning and mild global developmental delay, with marked intra-individual variability across domains. Motor development was significantly delayed and speech and language assessment demonstrated a pronounced receptive–expressive discrepancy. Sensory processing evaluation revealed a pattern of global sensory under-responsiveness, representing a novel and underreported feature in Tetrasomy X. Adaptive functioning was uneven, with relative strengths in daily living skills and weaknesses in motor abilities. Conclusions: This detailed early developmental characterization highlights the heterogeneity of Tetrasomy X and challenges some of the previous assumptions. The findings underscore the necessity of individualized, multidisciplinary assessment and early intervention to optimize developmental outcomes and quality of life in affected individuals. Full article

Background: Aging is characterized by a decrease in olfactory, attentional, memory, language, and visuospatial/executive abilities. In this context, our study aimed to evaluate the potential effects of Rosmarinus officinalis L. (rosemary) and Carum carvi L. (caraway) essential oils (EOs) on aging. First, we assessed, in 402 participants, the age-related changes in olfactory functions (odor threshold, discrimination, and identification), gustatory perceptions (sweet, sour, salty, and bitter taste), cognitive functions (focusing on attention, memory, language, and visuospatial/executive functions), and their possible correlations with aging. To achieve this, olfactory function, gustatory perception, and cognitive abilities were evaluated in healthy participants across different age groups. Then, to evaluate the age-related decrease in trigeminal function (59 participants), we used rosemary and caraway EOs that contain carvone, limonene, and 1,8-cineole, all of which are considered typical trigeminal stimuli. Methods: Olfactory function was assessed with the Sniffin’ Sticks test, gustatory function by the Taste Strips test, and rosemary and caraway EOs by the ratings of odor pleasantness, intensity, and familiarity using a labeled hedonic Likert-type scale. Results: Olfactory function could be a potential early indicator of attentional, memory, language, and visuospatial/executive dysfunctions. Our data indicated that rosemary and caraway EOs were perceived without any significant decrease in odor pleasantness, intensity, and familiarity ratings in relation to aging. Conclusion: Our results suggest the potential bioactive effects of rosemary and caraway natural EOs as a new strategy to promote healthy aging. Full article

Objectives: We aimed to compare performance-based functional ability and cognitive screening performance to determine the cortical thickness relationship in cognitively unimpaired (CN) elders, mild cognitive impairment (MCI) and dementia patients, as well as to compare performance-based and proxy-evaluated functional ability and to determine its cerebral white and gray matter correlates. Methods: In total, 22 CN, 32 MCI, and 21 dementia patients were included in this study. They underwent clinical, cognitive, and Magnetic Resonance Imaging (MRI) assessment. Individuals were evaluated with the Mini-Mental State Examination (MMSE), the Rey Auditory Verbal Learning test (RAVLT), the Activities of Daily Living Questionnaire (ADL-Q) and the Direct Assessment of Functional Status-Revised (DAFS-R). Results: Higher ADL-Q scores were significantly associated with lower cortical thickness (bilateral temporoparietal regions, including the inferior temporal lobes and precuneus), p < 0.05. The DAFS-R scale showed a relationship with greater cortical thickness across extensive regions of the bilateral frontal, parietal, and temporal cortices (p < 0.05). MMSE presented a more focal association, primarily in canonical memory-related areas, including the medial and lateral temporal lobes and inferior parietal regions (p < 0.05). Conclusions: Functional independence measured by ADL-Q was associated with frontal and parietal cortical thickness, while DAFS-R scores demonstrated a more diffuse evaluation of cortical atrophy. Additionally, performance-based functional abilities according to the DAFS-R appear to be a stronger marker of cortical thickness than ADL-Q and MMSE. Full article

Background: Early detection of modifiable risk factors for long-term care certification with dementia is essential. This study aimed to develop a risk-scoring tool using data from the Kihon Checklist and Questionnaire for the Late-Stage Elderly over a 2-year period to predict long-term care certification with dementia under Japan’s Long-Term Care Insurance system. Methods: Participants included 2041 functionally independent, community-dwelling older adults in Kure City, Japan, as of March 2021. A retrospective cohort study was conducted. Associations between KCL and LSEQ domains and certification for long-term care with dementia were examined using logistic regression. To improve practical use, a score chart was developed to predict certification for long-term care with dementia. Results: Two years after completing the Kihon Checklist and Questionnaire, 143 participants (7.0%) were certified for long-term care with dementia. Factors independently associated with certification for long-term care with to dementia included age, homebound status, cognitive decline, and locomotor decline. The prediction model, developed using these variables, showed excellent discriminatory ability, with an area under the curve of 0.790 (95% confidence interval: 0.754–0.827). Conclusions: We developed an effective predictive model for future long-term care certification with dementia using routinely collected administrative data. This tool may help healthcare providers and health planners identify older adults at increased risk of long-term care certification with dementia. Full article

Optical microscopy is a fundamental tool in the physical, chemical, and life sciences, enabling direct investigation of structure, dynamics, and function across multiple spatial and temporal scales. Advances in optical design, detectors, and computational techniques have greatly enhanced performance, but have also increased the complexity of modern microscopes, which are now software-driven and embedded in data-intensive workflows. Artificial intelligence has become an important component of this landscape, particularly through task-specific machine learning approaches for image analysis, optimization, and limited instrument control. While effective, these solutions are often fragmented and lack the ability to integrate experimental intent, contextual knowledge, and multi-step reasoning. Recent progress in large language models (LLMs) offers a new paradigm for intelligent microscopy. As foundation models trained on large-scale text and code, LLMs exhibit emergent capabilities in reasoning, abstraction, and tool coordination, allowing them to act as natural interfaces between users and complex experimental systems. This perspective highlights how LLMs can function as cognitive and orchestration layers that connect experiment design, instrument control, data analysis, and knowledge integration. Emerging applications include conversational microscope control, workflow supervision, and scientific assistance for data exploration and hypothesis generation, alongside important technical, ethical, and governance challenges. Full article

Number sense, the ability to rapidly perceive, estimate, and understand relationships between quantities, constitutes a fundamental basis for mathematical cognition. However, the extent to which it is modulated by top-down regulatory processes remains poorly understood. Rewards inherently carry quantitative attributes of abundance and scarcity, and prospect theory further suggests that individuals tend to underestimate rewards and overestimate punishments of equal magnitude, implying that the perception of reward quantities may be systematically biased. To address this issue, the present study employed EEG to examine how reward-related properties of stimuli modulate number sense, using socially relevant reward stimuli as experimental materials. Behavioral results demonstrated that rewarding stimuli were underestimated compared to neutral and punishing stimuli, while punishing stimuli were overestimated relative to neutral stimuli. EEG analyses revealed that at number-sensitive electrodes (PO7, PO8, Oz), the C1 component was sensitive to reward properties; the N1 component at PO7 was specifically sensitive to punishment; and in the P2p time window, neutral stimuli elicited the largest amplitudes, suggesting inhibitory processing of reward-related attributes during quantity perception. Together, these findings indicate that reward-based modulation of number sense occurs unconsciously and follows a dynamic temporal profile. Full article

This study examined associations between vocabulary knowledge, reading fluency, cognitive flexibility, and metacognitive monitoring accuracy in reading comprehension among fifth-grade students. Participants (N = 104) completed measures of cognitive–linguistic abilities and reading comprehension, with global metacomprehension judgments after reading and item-level confidence ratings. Metacognitive monitoring accuracy was assessed using calibration of global metacomprehension judgments and item-level confidence ratings. Calibration bias (confidence minus performance) indexed miscalibration direction, and its absolute value indexed calibration accuracy. Resolution reflected discrimination between correct and incorrect item-level responses. Structural equation modeling (SEM) was used exploratorily to examine theoretically motivated direct and indirect pathways via reading comprehension. Vocabulary knowledge showed the strongest associations with calibration accuracy and resolution, fully mediated by comprehension. Reading fluency showed a dual pattern: it contributed positively to resolution through comprehension, while also showing direct associations with lower calibration accuracy, indicating greater miscalibration and overconfident judgment tendencies among more fluent readers. Cognitive flexibility was not significantly related to any monitoring index. By jointly examining distinct indices of monitoring accuracy and separating comprehension-mediated from direct pathways, the study clarifies how cognitive–linguistic abilities may support or bias metacognitive monitoring in developing readers. Linguistic abilities, particularly vocabulary and fluency were central to students’ comprehension monitoring accuracy. Full article

With the rapid growth of e-commerce platforms, consumers increasingly make purchase decisions without direct physical interaction, particularly for tactile-dependent categories such as furniture and home décor. Drawing on embodied cognition, this study investigates how visual-based tactile cues influence consumers’ purchase intention on e-commerce platforms. Using experimental methods, two studies manipulate the level of visual-based tactile cues (high vs. low) and examine their effects on purchase intention. The results show that richer visual-based tactile cues significantly increase purchase intention. Contrary to traditional information overload assumptions that additional visual detail may hinder decision-making, this effect occurs through enhanced immersion rather than increased cognitive burden, suggesting that visual-based tactile cues operate as embodied sensory triggers instead of purely informational inputs. Furthermore, cross-modal mental imagery moderates this process in a counterintuitive way: the indirect effect of visual-based tactile cues on purchase intention via immersion is stronger when consumers’ imagery ability is lower, indicating a compensatory role of external sensory cues. By conceptualizing visual-based tactile cues as an innovation in interactive marketing within new media environments, this research offers actionable design implications for e-commerce platforms in enhancing tactile perception through visual presentation and improving conversion effectiveness. Full article

Peer action coordination in middle childhood is thought to benefit from socio-cognitive abilities such as emotion understanding and inhibitory control, but empirical evidence for their role is limited. This study replicates and extends a previous study by examining whether emotion understanding and inhibitory control correlate with children’s peer action coordination in a cooperative sensorimotor problem-solving task. To test this hypothesis, 6- to 10-year-old children (N = 108, M = 8 years, 8 months, 46.3% girls, 53.7% boys) completed the Test of Emotion Comprehension and the Attention Network Task. To assess children’s performance in coordinating their actions with a peer, they were asked to complete the Labyrinth Ball Game—a sensorimotor task that they first performed individually and then together with a peer. Contrary to expectations, there was no direct association between emotion understanding or inhibitory control and children’s peer action coordination after controlling for age, gender, and individual sensorimotor skills. However, a significant interaction between age and gender revealed that older boys showed greater cooperative action coordination performance than younger boys, whereas girls’ performance remained stable across age. These findings challenge the view that individual socio-cognitive abilities straightforwardly support cooperative success, suggesting that peer action coordination in middle childhood may rely on more complex mechanisms, such as gender-specific communicative strategies or social play, rather than on emotion understanding and inhibitory control. Full article

Artificial intelligence (AI) is profoundly reshaping labor market structures and occupational value evaluation systems. As a core group about to enter the workplace, university students’ perceptions of occupational social status are crucial for their career development and the alignment between education and the labor market. Study 1 explores how layoff risks and AI as a threat shape status evaluation. Study 2 investigates how AI’s role in jobs alters perceptions of status indicators and cognitive work type. The results show that students primarily attribute occupational social status to personal ability and organizational hierarchy rather than AI; A more positive attitude toward AI is associated with a greater propensity for pursuing routine cognitive occupations in the future; AI exerts an inverted U-shaped influence on occupational status indicators, with non-routine cognitive occupations experiencing an earlier decline in status but still maintaining higher ratings than routine cognitive occupations. These findings indicate that university students hold an overall positive yet contradictory attitude toward AI’s impact on occupational social status, which is inconsistent with actual employment trends. Therefore, researchers and policymakers should provide more comprehensive guidance to help students understand and adapt to AI-driven changes. Full article

The purpose of this study is to explore how adolescents in self-contained classrooms or schools for students with autism or ADHD, with no prior involvement in criminality, perceive and interpret different forms of early offending behavior through fictional case stories. The study specifically aims to examine their ability to discern what constitutes offending behavior, based on the double empathy problem. In total, 13 participants currently receiving secondary-level education (grades 10–12, aged 16–20 years) in self-contained classes at schools for adolescents with autism or ADHD participated. No student had cognitive disabilities or had been involved in any criminal act or criminal justice issues. The students were individually given three fictional written cases of offending behavior (theft, physical assault, and sexual assault). Audio-recorded stimulated recall interviews were obtained while the students solved tasks in relation to the cases, and these were analyzed to capture whether and what aspects of early offending were discerned. Overall, the results indicated limited awareness and enhanced social vulnerability, risking unwitting engagement in early offending behavior. Adapting social science education to students’ special educational needs to understand social interactions might be used to prevent and enhance their awareness of early offending behavior. Full article

Background: Although there is substantial research into individual nutrients during pregnancy, such as folate, iron, and vitamin D, little is known about the impact of mixtures of essential nutrients. We investigated the associations between mixtures of maternal essential minerals and vitamin concentrations and child cognition and executive functions at age 7. Methods: Data from 348 mother–child pairs in the Growing up in Singapore Towards Healthy Outcomes birth cohort with both plasma nutrient and neurodevelopmental outcome data were used. Gestational fasting plasma samples between 26 and 28 weeks of gestation were analyzed for 10 essential minerals and 12 B and D vitamers. Child cognition and executive functions at 7 years were assessed using the Wechsler Abbreviated Scale of Intelligence 2nd Edition (WASI-II) [n = 331] and the Behavior Rating Inventory of Executive Function 2nd Edition (BRIEF-2) [n = 348], respectively. Generalized weighted quantile sum regression (gWQS) was used to investigate the associations between nutrient mixtures and child cognitive executive function scores. Single-nutrient analysis using covariate-adjusted multivariable regressions was performed as a sensitivity analysis. Results: A one-quartile increase in the positively weighted nutrient mixture index was associated with higher block design T-scores (β = 2.17, 95% CI: 0.03, 4.31). Additionally, the negatively weighted mixture was associated with lower block design (β = −2.25, 95% CI: −4.92, 0.41, p = 0.02) and perceptual reasoning (β = −1.94, 95% CI: −5.17, 1.29, p = 0.04) scores in boys only. We found no association between the nutrient mixture and BRIEF-2 subscale T-scores. Conclusions: In this study, we found that a positively weighted nutrient mixture index of maternal gestational minerals and vitamins was associated with a greater ability in children to analyze and understand abstract visual items. Full article