Search Results (14,535)

Individual differences in circadian preference have been shown to influence cognitive functioning, yet their relationship with subjective memory complaints remains unclear. The present study examined the association between chronotype and everyday memory complaints in a sample of Portuguese adults, exploring the sequential mediating roles of sleep quality and psychological distress. A total of 382 participants completed self-report measures of chronotype, sleep quality, psychological distress (anxiety, depression, and stress), and subjective memory complaints. In a cross-sectional self-report design, a path analysis approach was used to test a theoretically driven serial mediation model. Results indicated that greater morningness predicted better perceived sleep quality, which in turn was associated with lower levels of psychological distress. No significant direct effects of chronotype or sleep quality on subjective memory complaints were observed; however, a significant indirect effect was identified through the sequential pathway linking chronotype, sleep quality, and psychological distress. These findings suggest that circadian preferences are associated with self-perceived memory functioning primarily through sleep-related and emotional mechanisms; however, the sequential mediation identified reflects associational rather than causal relationships. The model highlights the central role of sleep quality and emotional state in shaping subjective memory complaints and supports integrative approaches that consider both circadian and emotional factors. Full article

Substance use disorder (SUD) is a global problem with serious psychological, physiological, and social consequences. Seeking professional help is often delayed due to a lack of self-recognition of addiction, frequently sustained by self-deception. Although self-deception is a core feature of SUD, the mechanisms underlying it remain insufficiently studied. This research examines the role of impulsivity and self-efficacy in predicting self-deceptive behaviors—manipulation and mystification—in individuals undergoing addiction rehabilitation. The sample consisted of 122 Spanish participants from therapeutic communities (Mage = 44.99, SD = 10.58; 82.8% male) who completed the Self-Deception Questionnaire (SDQ-12), the Impulsive Control Scale Ramón y Cajal (ECIRyC), and the Drug Taking Confidence Questionnaire (DTCQ). Results showed that impulsivity significantly predicted both manipulation and mystification. Manipulation was also associated with self-efficacy in managing temptation and duration of addiction, highlighting its multifaceted nature. In contrast, mystification was predicted solely by impulsivity, suggesting a stronger dependence on internal psychological processes rather than contextual factors. These findings underscore the importance of targeting impulsivity and enhancing self-efficacy in addiction treatment. Interventions such as Cognitive Behavioral Therapy (CBT), Acceptance and Commitment Therapy (ACT), and mindfulness-based approaches may be particularly effective in reducing self-deceptive behaviors and supporting long-term recovery. Full article

This study investigates how bio-inspired versus sustainability-focused framing influences lay evaluations of a specific bio-inspired building-technology scenario, testing the empirical validity of the so-called “biomimetic promise”. Employing a between-subjects experimental design ($N=582$), we examined assessments of a weather-responsive self-shading façade across bio-inspired, sustainable, and neutral framing conditions. We developed and validated the 12-item Perceived Bio-Inspiration Scale (PBS)—a novel standardized psychometric instrument designed to quantify lay recognition of biomimetic features across visual, intentional, and naturalistic dimensions. While results showed robust direct framing effects, we identified a significant negative spillover: emphasizing biological inspiration significantly reduced the technology’s perceived sustainability, while sustainability framing diminished its perceived bio-inspiration. These findings demonstrate, in this façade context, that laypersons evaluate bio-inspiration and sustainability as cognitively distinct and potentially competing constructs, indicating that “natural-is-better” bias is not universal across all technology domains. Consequently, merely invoking biological origins is insufficient to enhance a technology’s ecological appeal. To foster public trust, science communication should shift from abstract biological metaphors toward a performance-driven communication strategy that prioritizes the disclosure of verifiable life-cycle assessment and specific operational advantages over symbolic nature-based analogies. Full article

As populations around the world continue to age, promoting healthy ageing has become a key public health priority. Nutrition plays a vital role in maintaining physical and cognitive function later in life, and omega-3 polyunsaturated fatty acids (PUFA) are essential components of cell membranes and are known for their anti-inflammatory and cardio-protective effects. Chronic inflammation and oxidative stress are major contributors to age-related decline, and omega-3s help mitigate these processes by modulating immune responses and improving endothelial function. This systematic review aims to examine the potential of omega-3 fatty acids to reduce inflammatory markers and improve overall health. Moreover, it aims to present the most effective dietary interventions in dairy cows that increase PUFA content in milk. PubMed, Web of Science, Scopus, and the Cochrane Library databases were searched for relevant articles published up to November 2025. Evidence suggests that older adults who consume higher levels of PUFA tend to have better cardiovascular health, preserved cognitive function, and a lower risk of age-related diseases such as Alzheimer’s and arthritis, and reduce the risk of frailty and disability in later years. Dietary manipulation to enhance PUFA in bovine milk represents a promising strategy for improving human nutrition while potentially benefiting cow health. Full article

In today’s AI-driven world, nurturing students’ capacity for independent, self-reflective learning is vital. They must build lifelong learning skills and develop personalized strategies through ongoing self-regulation. In this study, we employed a learning journal template to support self-regulated physics learning, highlighting the role of homework assignments designed to target different levels of cognitive domains. Our learning journal-supported approach aims to facilitate students’ preparation for lessons at home. Guided questions help students review the content covered in previous classes and reflect on the effectiveness of the instructional methods applied. The intervention focused specifically on the physics topic of dynamics, examining how students’ conceptual understanding and performance developed within this domain. The efficacy of this approach was tested among 7th- and 9th-grade students. Results indicate that the learning journal-based method, combined with structured homework, had a positive impact on students’ performance within the topic of dynamics. Full article

Spontaneous combustion in goaf areas poses a significant threat to coal mine safety. Traditional safety management systems, reliant on passive response and single-indicator thresholds, often suffer from delayed warnings and lack cognitive decision support. To address this challenge, this study proposes a big-data-driven cognitive computing framework for dynamic risk prediction of goaf spontaneous combustion, based on a “Cloud-Edge-End” collaborative architecture. The method leverages multi-sensor big data streams (CO, C₂H₄, O₂, etc.) and deploys a lightweight Radial Basis Function (RBF) neural network on underground edge computing nodes (STM32) for real-time analytics. The model demonstrates excellent predictive performance on imbalanced datasets, with a PR-AUC of 0.910 and a recall of 99.7%. The edge-deployed RBF model achieves a single-pass inference time of only 0.62 ms, enabling real-time cognitive risk mapping. Field application at Z Coal Mine validated the system’s effectiveness, providing an average pre-warning time of 48.5 h, achieving zero spontaneous combustion accidents, and reducing the Total Recordable Injury Rate (TRIR) by 15.2%. This work illustrates how edge-based cognitive computing can transform safety management from passive response to proactive prevention, offering a scalable and interpretable framework for intelligent mine safety. Full article

This study examines how architectural acoustic environments of university buildings influence student learning outcomes from a sustainability perspective. In the context of sustainable campus development and indoor environmental quality (IEQ), acoustic conditions represent a critical yet often overlooked factor affecting cognitive performance and well-being. Through subjective questionnaires and objective assessments, we analyzed the acoustic experiences of 180 undergraduates, investigating the effects of varying noise levels (45 dBA, 60 dBA, and 75 dBA) and noise types (traffic and conversation) on learning outcomes during study sessions. This study aims to quantify acoustic sustainability in buildings of higher education and provides preliminary evidence that may inform sustainable campus planning and building design. Findings indicate that, within the experimental conditions of this study, regardless of the type of noise, higher noise levels are correlated with reduced subjective satisfaction and diminished learning outcomes. Specifically, traffic noise was found to have a stronger negative impact on memory, while conversational noise significantly impaired attention and reading ability. Additionally, an interaction effect was observed between noise type, noise level, as well as student gender, with male participants showing greater susceptibility to variations in noise level and type. These findings provide preliminary evidence for further improving sustainable campus planning and building design. Full article

CDKL5 Deficiency Disorder (CDD) is a severe neurodevelopmental encephalopathy characterized by early disruptions of synaptic maturation and network stability, leading to persistent motor, cognitive, and behavioral impairments. Given the role of the endocannabinoid system in synaptic development, neuroinflammation, and neuronal resilience, we investigated whether the sustained enhancement of endogenous 2-arachidonoylglycerol (2-AG) signaling via monoacylglycerol lipase (MAGL) inhibition could mitigate key pathological features in adult Cdkl5 knockout (KO) mice. Using an intermittent 6-week treatment, the MAGL inhibitor JZL184 robustly increased plasma 2-AG levels, reduced MAGL protein levels, and activated CB1-AKT signaling without evidence of receptor desensitization. Despite this clear pharmacodynamic efficacy, behavioral effects were domain-specific: neither dose ameliorated core behavioral deficits, although the higher dose selectively reduced stereotypic jumping and modestly improved cue-dependent associative memory. At the cellular level, JZL184 induced biologically meaningful effects, partially restoring dendritic spine maturation in the primary somatosensory cortex and increasing neuronal survival in the vulnerable CA1 hippocampal region. In contrast, microglial responses were dose-dependent and divergent, with the lower dose exerting anti-inflammatory effects, while the higher dose increased cortical microglial density and Allograft Inflammatory Factor-1 (AIF-1) expression, suggesting engagement of compensatory or off-target mechanisms. Overall, these findings show that MAGL inhibition activates neuroprotective pathways and ameliorates select structural deficits in adult Cdkl5 KO mice, but is insufficient to produce broad behavioral recovery, highlighting the domain-specific effects of selective 2-AG enhancement via MAGL inhibition and the need for developmentally informed or multimodal therapeutic strategies in CDD. Full article

Background/Objectives: Mild cognitive impairment (MCI) is common in Parkinson’s disease (PD) and significantly impacts quality of life. Non-invasive brain stimulation (NIBS) techniques have emerged as potential therapeutic interventions. This systematic review analyzes the current evidence regarding the efficacy of Transcranial magnetic stimulation (TMS) and transcranial electrical stimulation (tES) on cognitive domains in patients with PD-MCI. Methods: A systematic search was conducted across the PubMed, Scopus, Web of Science, and Medline Ultimate databases up to 20 November 2025. We included studies investigating the effects of NIBS compared to sham stimulation on neuropsychological outcomes in diagnosed PD-MCI patients. Results: Eight studies involving different stimulation protocols were included. Interventions primarily used TMS or tES targeting the left dorsolateral prefrontal cortex (DLPFC). Episodic memory and global cognition were the most responsive domains, assessed with specific neuropsychological scales. Findings for executive functions and attention were heterogeneous, while visuospatial abilities generally showed limited immediate response. Conclusions: NIBS represents a promising but low-certainty-evidence adjunctive therapy for PD-MCI, with improvements found in memory and global cognition. Future research should prioritize larger sample sizes, combined interventions (NIBS plus cognitive rehabilitation), and extended follow-ups to evaluate long-term neuroplasticity. Full article

Background/Objectives: Developmental language disorder (DLD) has widespread and persistent consequences for children’s development, extending beyond language. Quality of life (QoL) can also be affected, potentially related to difficulties with cognition (e.g., language ability), behaviour (e.g., social–emotional functioning), and/or environmental factors (e.g., multilingualism). This study set out to characterise changes in the QoL of children with DLD and to identify related factors. Methods: Data were collected at 4 and 9 years from children who had attended early language intervention groups before age 4. Parents completed online questionnaires, including the KINDL for QoL. The KINDL measures QoL on six domains: physical well-being, emotional well-being, self-esteem, family well-being, social well-being, and school functioning. Structural Equation Modelling (SEM) was used to assess the relationship between change in QoL and cognitive, behavioural, and environmental factors. Results: At both time points, the QoL of children with DLD was reduced compared to the normative group on all domains except self-esteem and family. Emotional well-being and self-esteem scores were significantly lower at 9 years compared to 4 years. Peer problems and multilingualism emerged as influential factors regarding changes in QoL over time. Conclusions: The QoL of children with DLD is vulnerable between age 4 and 9. Overall, QoL might deteriorate in this period, specifically emotional well-being. Early peer problems and multilingual status influence the changes observed in different aspects of QoL, although these effects should be interpreted with caution. Full article

Background/Objectives: Cognitive impairment affects multiple brain functions, and its early detection is essential to prevent progression to dementia; artificial intelligence has shown considerable potential in this field. This scoping review aims to map the impact of artificial intelligence–based tools for the early detection of cognitive impairment by identifying the main technologies used, examining their effectiveness, and exploring their ethical implications. Methods: A scoping review was conducted between April and May 2025 following the PRISMA-ScR methodological framework; the review protocol was previously registered on the Open Science Framework. PubMed, Scopus, and Cochrane databases were searched using natural language and controlled vocabulary terms via Medical Subject Headings. The search was limited to articles published between 2020 and 2025, in English or Spanish, with free full-text access. Methodological quality was assessed using CASPe, JBI, and MMAT. Results: A total of 14 studies were included after the selection and critical appraisal process. The findings show that artificial intelligence–based tools such as deep-learning models applied to neuroimaging, speech and gait analysis, electronic health record analysis, and mobile health applications demonstrate promising accuracy in detecting early cognitive changes. These technologies enable the identification of subtle patterns that may be difficult to detect using conventional clinical assessments. Conclusions: AI-based tools can provide substantial support for clinical decision-making by effectively identifying subtle changes that are imperceptible to human intelligence. However, their use also raises ethical issues related to patient privacy and data security. Full article

Background/Objectives: Daily sleep patterns are associated with cognitive health and Alzheimer’s disease (AD). However, it remains unclear how suboptimal irregular sleep manifests in AD from the preclinical stage to dementia. This study aimed to establish the dose–response association between sleep irregularity and psychometrically defined stage-specific AD as well as executive dysfunction, among adults with subjective cognitive and sleep issues. Methods: Cross-sectional data were obtained from 532 Japanese adults (mean age = 63.9 years) between March 2023 and April 2024. Sleep irregularity was quantified using the Sleep Regularity Index (SRI) with 24/7 accelerometer data. A modified Poisson regression with cubic splines was performed to establish the dose–response association. Results: This study identified novel non-linear associations. The prevalence ratios of cognitive impairment, defined as being in the preclinical and more advanced stages of AD, significantly declined beyond a median SRI of 60. Participants within this SRI range also showed significantly lower prevalence ratios of poorer Trail Making Test B performance. All results were independent of age, sleep duration, and risk of depression. Conclusions: Maintaining balanced-to-regular daily sleep patterns might be optimal for AD progress from its preclinical stages, with a potential benchmark at SRI of 60, especially for those individuals at risk for cognitive decline and sleep disorders. Further research is needed to replicate this benchmark in diverse populations and to evaluate the effect of rigid sleep regularity on cognitive health. Full article

Objectives: This randomized, double-blind, placebo-controlled 12-week clinical trial evaluated the efficacy and safety of a standardized ethanol extract of purple perilla leaves (Perilla frutescens Britton var. acuta Kudo; PE) in adults with cognitive impairment. Methods: Subjects who met the inclusion criteria were randomly assigned in a 1:1 ratio to one of two groups and received PE (n = 50, 500 mg/day) or placebo (n = 50) for 12 weeks. The primary efficacy outcomes included cognitive function, which was assessed by the Korean mini-mental status examination–2 (K–MMSE–2) and the Alzheimer’s disease assessment scale–cognitive subscale (ADAS–Cog), and plasma amyloid β (Aβ) and brain-derived neurotrophic factor (BDNF) levels, which were measured as secondary biochemical markers. The safety biomarkers were also assessed before and after the intervention. Results: After 12 weeks of intervention, the K–MMSE–2 total score, the K–MMSE–2 subdomain scores (attention and calculation and language), the ADAS–Cog total score, and the ADAS–Cog subscale scores (word recall, commands, delayed word recall, naming, word recognition, and recall instructions) showed statistically significant between-group improvements compared with the placebo group. Improvements were observed in both groups, whereas the magnitude of cognitive enhancement was greater in the PE group, indicating an effect beyond placebo-related responses. No statistically significant between-group differences were observed in plasma Aβ or BDNF levels. The safety evaluation found no clinically significant changes. Conclusions: Twelve-week administration of PE significantly improved cognitive outcomes without safety concerns, suggesting its potential as a standardized botanical ingredient for supporting cognitive function in individuals with early cognitive impairment. Full article

Traditional approaches to university-level history education often fail to provide immersive and interactive environments that foster deep cognitive engagement. To address these limitations, we developed an AI-enabled virtual museum system that integrates AI-generated content with knowledge graphs through a multi-layered architecture. The system architecture follows a three-tier framework: a front-end interaction layer (Unity/Unreal Engine) for real-time user engagement, a core service layer for intelligent event scheduling and response control (Chat General Language Model/Stable Diffusion), and a data and model layer (My Structured Query Language/MongoDB) to provide structured knowledge. To evaluate the system’s effectiveness, a four-week controlled experiment was conducted with 83 university students. The experimental group using the AI virtual museum showed a significantly higher mean post-test score (84.5 ± 6.8) than that of the control group (71.6 ± 7.9), with statistical significance at p < 0.001, starting from nearly identical baseline scores (61.2 and 60.4 for the experimental and control groups). Correlation analysis was conducted to identify scenario simulations (r = 0.59) and deep inquiry tasks (r = 0.54) as key drivers of learning mastery. By aligning advanced system engineering with educational theory, the results of this study offer a solution for high-fidelity, intelligent digital educational platforms, proposing a validated model for integrated system innovation in education. Full article

The primary aim of this study is to develop a comprehensive theoretical model for creating digital content that enhances speech formation in toddlers aged 1–3, based on children’s folklore. This model seeks to integrate pedagogical, psychological, and cultural elements to offer a balanced and age-appropriate digital learning experience for young children. The study employed a systematic literature review using Creswell’s seven-step process, which involved identifying relevant research, reviewing and analyzing 22 peer-reviewed studies published between 2019 and 2023, and synthesizing their findings. VOSviewer version 1.6.18, a bibliometric visualization tool, was used to conduct a keyword co-occurrence analysis, identifying key concepts and trends in digital content creation for toddlers. The systematic review adhered to the PRISMA framework to ensure rigor in the selection and analysis of the included studies, which spanned fields such as education, psychology, and pediatric development. The study identified several key dimensions necessary for developing an effective theoretical model of digital content creation for toddlers: The content must be age-appropriate and consider the unique cognitive, linguistic, and developmental needs of toddlers. Children’s folklore plays a crucial role in language development, offering culturally rich and rhythmically engaging material for young learners. The model must address the balance between screen time and real-world interactions, ensuring that digital engagement does not replace essential real-life learning experiences. Ensuring the psychological and physiological safety of digital content is paramount, requiring the exclusion of inappropriate or harmful material and the inclusion of interactive, engaging content that supports speech development. The study concludes that a well-designed model for digital content creation, rooted in children’s folklore, can significantly enhance speech development in toddlers. Such a model must not only support language acquisition but also reflect cultural heritage, promote safe digital environments, and encourage a balance between digital and real-world interactions. By integrating the findings from various disciplines, this theoretical model provides a holistic framework that can guide the development of high-quality digital content aimed at supporting early childhood language development in the digital age. Full article