Search Results (6,940)

This study illuminates fundamental questions in behavioral science through advanced machine learning methodologies applied to large-scale public opinion data. Drawing on Kahneman and Tversky’s dual-process theory and Sunstein’s nudge architecture, we employ hierarchical unsupervised clustering and supervised predictive models to detect cognitive biases—loss aversion, availability heuristic, and partisan motivated reasoning—embedded within a nationally representative survey of 5022 American respondents. Our primary methodological contribution is a hierarchical two-stage clustering framework that uncovers latent opinion structures without imposing a priori partisan categories, permitting discovery of cross-cutting cleavages invisible to conventional survey analysis. Three principal findings emerge: (1) loss aversion is empirically confirmed in prospective economic perception, with pessimists outnumbering optimists at a 1.14:1 ratio even among respondents rating current conditions positively; (2) partisan motivated reasoning produces a 13.15 percentage-point perception gap among individuals with identical financial circumstances; and (3) multi-platform digital engagement is associated with reduced partisan bias, providing evidence that challenges simple echo chamber assumptions. Crime safety perception emerges as the strongest predictor of economic bias, surpassing party affiliation, and substantiating availability heuristic dominance in political cognition. These findings carry implications for democratic accountability, platform governance, and the ethics of AI-augmented behavioral analysis in an era of affective polarization. Full article

Tactile working memory limits the amount of information that can be processed through touch, with important implications for the design of haptic communication systems. Although visual and auditory working memory have been extensively investigated, tactile working memory, particularly for spatial and spatiotemporal sequences, remains less well understood. The present study examined tactile working memory capacity in two psychophysical experiments. Participants reproduced sequential vibrotactile stimuli delivered to the forearm via a 3 × 3 array of voice-coil actuators by entering responses through keypresses. Both experiments employed an adaptive 3-up/1-down staircase procedure, in which sequence length was adjusted according to response accuracy, and thresholds were estimated from reversal points. In Experiment 1 (Ordered Recall), participants reproduced both the spatial locations and the temporal order of stimulation, yielding a memory capacity threshold of approximately four items. In Experiment 2 (Unordered Recall), participants recalled only the set of stimulated locations without regard to order, resulting in a higher threshold of approximately five items. These results demonstrate that incorporating temporal sequencing demands into spatial recall substantially increases cognitive load and reduces effective tactile memory capacity. The findings clarify fundamental limits of tactile working memory and provide practical guidance for the development of haptic interfaces, wearable feedback systems, and sensory substitution technologies that must balance information complexity with human cognitive constraints. Full article

Background: Subacute sclerosing panencephalitis (SSPE) is a chronic, progressive disease of the central nervous system (CNS) caused by persistent infection at this level with the wild measles virus. Its incidence is negatively correlated with measles vaccination coverage. The pathogenesis isn’t fully understood, but infection before the age of 2 is an important risk factor. Methods: This is a retrospective observational study conducted at the Louis Turcanu Emergency Children’s Hospital in Timisoara, Romania, based on the analysis of the medical records of patients diagnosed with SSPE between January 2021 and December 2025. We analyzed demographic and epidemiological factors, clinical and paraclinical findings, management, and outcomes. Results: Seven children were diagnosed during the study period, with a mean age of 8.4 years (range 7–11 years). Six of them had contracted measles during their first year of life, and one at the age of four. The mean latency period was 7.1 years (range 4–9 years). On admission, all patients presented symptoms consistent with clinical stage II, with periodic slow wave discharges on electroencephalogram (EEG). The initial brain Magnetic Resonance Imaging (MRI) was normal in two cases, while revealing varied abnormalities in all others. Despite complex treatment with isoprinosine and anticonvulsants, progressive cognitive and neurological deterioration continued in all patients. Conclusions: SSPE is a rare but serious, debilitating disease despite its complex, multidisciplinary care. Following a 10-year SSPE-free period, the reappearance of these pediatric cases constitutes a public health alert, unequivocally demonstrating the importance of measles vaccination. Full article

Background/Objectives: Age-related gut microbiota dysbiosis leads to systemic oxidative stress, chronic inflammation, and multi-organ functional decline. However, there is limited evidence supporting microbiota-based therapies for aging. This study aimed to examine the effect of gut microbiota from young donors, particularly those with increasing Bifidobacteria levels through dietary intervention, on age-related declines in fertility, cognition, and reproduction. Methods: We conducted experiments using gut microbiota from young human donors, with or without pre-conditioning with barley leaves (BL), to transplant into aged male mice. Hippocampal metabolome and behavioral assessments were used to identify differences in recognitive regulation during aging. Moreover, testis tissue, semen quality, and offspring studies were determined to investigate the beneficial effects on fertility and underlying mechanism. Conclusions: This preliminary dietary treatment promotes the growth of Bifidobacterium in aged recipient mice. Aged male mice received young fecal microbiota transplants (yFMTs), BL-conditioned yFMTs (BLyFMTs), and a combined treatment of BLyFMT plus recipient BL supplementation. The combined approach significantly increased intestinal Bifidobacterium levels and effectively restored hippocampal metabolomic profiles and cognitive behavior. Additionally, yFMT-based treatments mitigated structural damage to the seminiferous tubules and prevented the germ cell depletion. Consistently, those interventions improved sperm quality and mechanistically enhanced hypothalamic–pituitary–gonadal (HPG) axis activity in aged recipients. These findings highlight Bifidobacterium as a key factor in microbiome-driven rejuvenation, enhancing the effectiveness of yFMTs in addressing aging-related declines. Full article

In the new industrial revolution 5.0 era, manufacturing facilities with manual assembly have higher expectations, higher mass customization, and more human involvement, as well as including new digital technologies in smart workstations. Given these expectations, the cognitive load of manual assembly workers is increasing. Cognitive assessment systems are being added to manufacturing facilities to work in parallel with physical and sensory assistance systems to establish better work conditions for workers and better overall system performance. This paper presents an exploratory study using eye-tracking as an assessment system to identify potential locations of increased cognitive workload and errors to better understand where and how to employ assistance for workers to improve the manual assembly and inspection process. The results of this study indicate that the highest workload occurs with measuring and inspection tasks, and most errors occur during the assembly of parts, where their geometry impacts placement. It also demonstrates the feasibility of eye-tracking as a low-cost, integral part of the human–computer system in the assembly environment. Full article

As generative artificial intelligence (AI) becomes increasingly involved in creative processes, designers encounter a fundamental tension regarding creative control—the degree to which they dominate design direction and iterative decision-making when collaborating with AI. Existing theories offer contradictory predictions: self-determination and psychological ownership theories emphasize the benefits of control, whereas cognitive load theory highlights its cognitive costs. This tension remains empirically unresolved, particularly regarding how designer characteristics shape these competing effects. This study examines the dual-pathway mechanism linking creative control to design creativity and investigates the moderating role of design experience. A scenario-based between-subjects experiment was conducted with 226 designers and design students. Creative control exerted a positive indirect effect on design creativity through psychological ownership (effect = 0.16, 95% CI [0.09, 0.24]) and a negative indirect effect through cognitive load (effect = −0.07, 95% CI [−0.14, −0.02]), confirming the double-edged sword effect. Design experience strengthened the positive pathway while buffering the negative pathway. Creative control thus functions as a double-edged sword in designer-AI co-creation, with its net effect contingent on designer expertise. The results extend Conservation of Resources theory to human-AI collaboration contexts and inform the design of experience-adaptive AI-assisted systems. Full article

Food waste presents a major challenge to global sustainability. Up to 60% of this waste occurs at the household level, at which point labeling confusion causes avoidable loss. The present study employed the motivation–opportunity–ability framework to conduct a narrative synthesis of 82 studies and pieces of gray literature, incorporating policies and industry practices to elucidate how food labeling modulates food waste behavior through interactions with consumer motivation, external opportunities, and individual abilities. Food labeling should be considered a systemic intervention tool spanning the entire food supply chain rather than mere carriers of information. The present findings indicate that although standardizing quality and safety label terminology mitigates cognitive confusion, it may have limited efficacy to reduce food waste. Extending shelf life and providing explicit storage guidance are critical strategies that are often undervalued and comparatively underexplored. Labels most effectively reduce waste when they simultaneously activate motivation, opportunity, and ability. When all three elements cannot be activated concurrently, stakeholders should prioritize improving external opportunities or enhancing individual abilities rather than stimulating motivation. Food labeling interventions can only be effective at waste mitigation if systemic and transdisciplinary synergy is achieved among all stakeholders in food supply chains. Full article

Early-stage remote site analysis is often hindered by fragmented media that fail to convey sufficient spatial context to off-site collaborators. To address this challenge, we propose SiteSync, a real-time remote collaborative system that combines live video, coarse mesh streaming, georeferenced pose tracking, and 3D spatial annotations to establish a shared spatial understanding between on-site and remote collaborators. The system was evaluated through a counterbalanced within-subject study with 24 participants, comparing the synchronous SiteSync workflow against a traditional asynchronous baseline. The results showed that SiteSync significantly improved task performance by reducing completion time and rework while increasing overall accuracy (all p < 0.001). Participants also reported lower cognitive workload and higher usability. Remote users benefited most significantly. These findings show that the synchronous workflow can improve collaboration efficiency and user experience in early-stage site analysis. Full article

Objective: To investigate the integrated relationship between Cerebral Small Vessel Disease (CSVD) markers and quantitative facial soft-tissue measurements in Alzheimer’s disease (AD) continuum, utilizing peripheral muscle health as a potential biomarker for systemic frailty and neurodegeneration. Methods: Retrospective analysis of 3T brain MRI data from 67 patients (AD, N = 45; Mild Cognitive Impairment [MCI], N = 22). CSVD markers were assessed using STRIVE and standardized scales (Fazekas, Potter). Facial soft-tissue metrics, including masseter and tongue volume, temporal muscle thickness (TMT), and fat infiltration (Mercuri Scale), were quantified via semi-automatic segmentation on T1-weighted sequences. Group comparisons (AD vs. MCI) used regression models adjusted for age and sex. The overall central–peripheral relationship was explored via Canonical Correlation Analysis (CCA). Results: The AD group showed a highly significant cognitive decline (MMSE: 23.2 ± 4.1 vs. 28.2 ± 1.4, p < 0.0001). Centrally, the presence of PVSs in the mesencephalic region was the most robust predictor for AD (p = 0.003). Peripherally, average masseter muscle volume was significantly lower in the AD group (p = 0.0273), and masseter fat infiltration was significantly higher (p = 0.025), supporting localized sarcopenia. The CCA demonstrated a statistically significant positive multivariate relationship (r = 0.51, Roy’s Largest Root p = 0.015) between a higher combined CSVD burden and a worse soft tissue profile across the cohort. Conclusions: Quantitative indices of facial soft tissues, particularly masseter muscle volume and quality, reflect systemic frailty and cognitive deterioration along the AD continuum. The strong central–peripheral correlation suggests that sarcopenia and CSVD are interconnected manifestations of a shared pathobiological process. These easily measurable facial markers could serve as valuable, non-invasive peripheral biomarkers, complementing traditional neuroimaging risk stratification in AD. Full article

Generative Artificial Intelligence (GenAI) is reshaping how students engage with learning both within and beyond traditional classroom settings. In a time when the development of transferable skills is essential for enabling students to thrive in varied and rapidly evolving environments, the potential of GenAI to enhance learning engagement remains insufficiently understood. Despite rising interest in interactive, personalised learning companions that enable deep engagement and ongoing skills development, scholarly research remains limited. This gap constrains effective institutional use of GenAI, reinforces black-box thinking, and restricts understanding of meaningful student engagement and skills acquisition. This paper investigates how a GenAI-enabled AI teacher supports student learning engagement, focusing on behavioral engagement as evidenced by learner interaction and participation patterns across diverse international higher education institutions. Using a combination of quantitative engagement metrics and qualitative learner reflections, the study examines how GenAI supports personalised learning, sustained interaction, autonomy, and cognitive engagement among students with varying educational backgrounds. The findings demonstrate that GenAI-based teaching systems can promote meaningful learning engagement, enhance motivation, and strengthen the development of transferable and employability skills. The study contributes empirical evidence to current debates on GenAI integration, teacher practices, and student engagement, offering implications for curriculum design and institutional adoption of GenAI-enabled learning tools. Full article

Background: Sjögren’s disease (SjD) is a chronic systemic autoimmune disorder characterized by persistent exocrine gland inflammation, possible multi-organ involvement and a marked predominance of mid-life women. Beyond dryness and fatigue, patients report mood disturbances and cognitive complaints such as “brain fog”, which affect daily functioning and quality of life. Objective: To summarize and critically synthesize the literature on depression, anxiety, cognitive function, personality traits and quality of life assessment in adults with SjD and to highlight clinically relevant gaps. Methods: We performed a narrative review (PubMed, Cochrane, Embase through June 2025) of studies on psychological outcomes, cognitive function and quality of life in adults with SjD. Results: Depression and anxiety were frequently observed: depressive symptoms were present in roughly one-third to nearly half of patients, while anxiety symptoms were reported by about one-third. Cognitive impairment (affecting memory, attention and executive function) was also frequently described, often alongside severe fatigue and sleep disturbance. Overall, quality of life was reduced in SjD, driven mainly by fatigue and emotional distress rather than by classic disease activity. Neuroimmune mechanisms (e.g., chronic systemic inflammation and cytokine signalling such as IL-6 and TNF-α) may contribute to affective and cognitive symptoms. Overall, the evidence base remains largely cross-sectional and heterogeneous. Conclusions: Psychiatric symptoms and cognitive complaints represent a substantial and clinically relevant burden in SjD. Routine screening and multidisciplinary management that includes psychological assessment and support may improve well-being, adherence and quality of life. Full article

Background: Alzheimer’s disease (AD) is a multifactorial neurodegenerative disorder characterized by amyloid-β aggregation, tau hyperphosphorylation, oxidative stress, and mitochondrial dysfunction. Emerging evidence indicates that the gut microbiota plays a critical role in modulating neuroinflammatory, and metabolic pathways involved in AD pathogenesis through the microbiota-gut-brain axis. Objective: This systematic review aims to comprehensively evaluate the role of the microbiota-gut-brain axis in Alzheimer’s disease, with a particular focus on its mechanistic links to oxidative stress, mitochondrial dysfunction, and amyloid pathology, as well as its therapeutic potential. Methodology: A comprehensive literature search was conducted using PubMed, Scopus, and Web of Science databases, focusing on studies evaluating gut microbiota composition, metabolomic changes, oxidative stress markers, mitochondrial activity, and therapeutic interventions in AD models and patients. Results: Altered gut microbial composition in AD is associated with increased pro-inflammatory taxa (Escherichia-Shigella, Bacteroides) and depletion of short-chain fatty acid (SCFA) producing bacteria (Faecalibacterium, Roseburia). Dysbiosis contributes to systemic inflammation, disrupted intestinal permeability, and microglial activation, leading to oxidative damage and mitochondrial impairment in neurons. Preclinical and clinical studies indicate that probiotics, prebiotics, and fecal microbiota transplantation can restore redox balance, reduce neuroinflammation, and improve cognitive outcomes. Multi-omics and AI-based models are emerging as tools for identifying microbiome-derived biomarkers for early AD detection. Conclusion: The gut microbiota-mitochondria-oxidative stress axis represents a promising therapeutic target in Alzheimer’s disease. Future research should focus on longitudinal human studies, standardized microbial profiling, and personalized microbiome-based interventions to translate these mechanistic insights into clinical benefit. Full article

Background: Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a debilitating disorder, characterized by symptoms such as post-exertional malaise (PEM) and cognitive impairments. This study assessed reaction time (RT) metrics in three-dimensional (3D) visual tasks with the aim of objectively quantifying the cognitive impairments in ME/CFS patients compared to controls. Methods: A total of 120 participants (60 ME/CFS patients and 60 controls) were recruited at the Department of Ophthalmology, Universität of Erlangen-Nürnberg. RT was assessed using a virtual reality–oculomotor test system, presenting 3D stimuli at three disparity levels (275″, 550″, and 1100″) within three gaming repetitions (R1, R2, and R3). Mixed-effects models were used to evaluate group differences, with age and gender as covariates. Pairwise contrasts were calculated to assess changes across repetitions. Fatigue self-assessments were recorded by validated questionnaires, (FACIT Fatigue Scale, Chalder Fatigue Scale, Bell Score and Health Assessment Questionnaire), and their correlation with RT metrics was portrayed using a Spearman correlation matrix. Results: Estimated means (EM-means) for RT were significantly prolonged in ME/CFS patients compared to controls at disparity 275″ (1969 ms vs. 1384 ms; p = 0.0001), 550″ (1409 vs. 1071 ms; p = 0.0012) and 1100″ (1126 ms vs. 891 ms; p = 0.00223). Age was a significant covariate (p < 0.001), while gender showed no effect. Both groups demonstrated improvements in RT over repetitions; however, ME/CFS patients showed a significantly lower improvement compared to controls, reaching significance in R3 (p = 0.0042). RT metrics did not correlate with patients’ self-assessment scores. Conclusions: ME/CFS patients showed consistently slower RTs compared to controls, particularly in later, easier gaming repetitions, potentially reflecting the impact of fatigue. Full article

Pruning is a critical horticultural practice that requires continuous interpretation of plant structure to maintain crop health and prevent disease. Manual identification of pruning-relevant regions is labor-intensive and limits scalability in precision agriculture. This study presents a cognitive vision-based pruning region identification system using a You Only Look Once version 9 model to detect lateral branches, lower leaves, and diseased leaves in Solanum lycopersicum. A custom dataset of 4905 augmented images was used for training and evaluation. The model achieved 82.86% precision, 77.24% recall, 79.96% F1-score, and 83.21% mAP. Deployment on Raspberry Pi 5 demonstrated real-time, cloud-independent edge inference, indicating the feasibility of low-cost cognitive vision systems for smart agriculture. Full article

In response to the redundant spatio-temporal modeling and insufficient adaptation to dynamic decision-making in eye-tracking interaction of smart home interfaces, a smart home interface eye-tracking response optimization model based on spatio-temporal Transformer and gate control cross-attention is proposed. It adapts the physiological characteristics of eye-tracking jumps through dynamic sparse attention gating to compress computational redundancy and combines multi-objective reinforcement learning attention modulation to construct a closed-loop decision-making mechanism, optimizing interface parameters in real-time. Experiments showed that the model reduced eye-tracking trajectory prediction error by 23.7% compared to advanced benchmarks, increased the success rate of adapting to dynamic mutation scenarios to 89.2%, and controlled performance fluctuations within 2.3% under noise interference. In high-fidelity user testing, the accuracy of cross-task gaze transfer reached 93.4%, the failure rate of glare interference was optimized to 2.4%, and the user cognitive load index was reduced by 27.9%. Its resource consumption and energy consumption were reduced by 26.7% and 44.9%, respectively, while its posture deviation tolerance remained at 3.5°. The sparse spatio-temporal modeling of the spatio-temporal adaptive Transformer module and the enhanced gating mechanism of the hierarchical gated cross-attention module work together to break through the limitations of traditional methods in computational efficiency and dynamic feedback, providing high-precision and low-latency eye-tracking interaction solutions for smart home interface systems, and promoting the practical evolution of personalized human–machine collaborative control. Full article