Search Results (164)

Background/Objectives: Detecting Alzheimer’s disease (AD) from normal aging using eyes-open (EO) EEG is challenging due to stimulus-driven nonstationarity and fragmented oscillatory responses. This study aims to determine whether prototype-based representations derived from Dynamic Mode Decomposition (DMD) can improve AD detection from EO photostimulation EEG. Methods: We propose a DMD-based framework termed DMD-based Clustered Pattern Projection (DMD-CPP). Segment-wise DMD representations were clustered to learn class-specific medoid prototypes, and each EEG epoch was encoded as a vector of cosine-similarity coordinates with respect to these prototypes. A linear SVM classifier was trained on the resulting DMD-CPP features and evaluated under strict leave-one-subject-out validation. Results: The DMD-CPP model achieved competitive classification accuracy and, importantly, enhanced margin-based reliability. In EO photostimulation, AD versus healthy control classification showed a pronounced improvement, characterized by wider and more asymmetric decision margins, particularly assigning low confidence to normal epochs misclassified as AD. Tasks involving frontotemporal dementia also showed improvement, although the effect was less pronounced than for AD. Conclusions: Clustering-based pattern projection has been shown to stabilize EEG dynamics and provide an interpretable, confidence-aware feature representation. These findings suggest that DMD-CPP offers a promising framework for reliable AD detection from EO EEG, where conventional spectral methods typically struggle. Full article

Background/Objectives: Perceptual awareness and decision formation unfold gradually as sensory evidence increases. Near the threshold of awareness, small differences in neural processing efficiency can be amplified into marked behavioral variability. Open-skill athletes are trained to make rapid decisions under dynamic and uncertain conditions, yet it remains unclear whether their perceptual advantage reflects enhanced early sensory sensitivity or more efficient late-stage evidence accumulation. This study aimed to identify the processing stage at which open-skill sports expertise exerts its influence. Methods: Twenty-five open-skill athletes and twenty-three non-athlete controls completed a visual orientation discrimination task with eight graded levels of stimulus visibility, ranging from subliminal to clearly visible. Behavioral performance was analyzed together with hierarchical drift–diffusion modeling to estimate latent decision parameters. Event-related potentials (ERPs) were recorded using a 64-channel EEG system during an active decision task and a passive viewing task, focusing on early (N2, P2) and late (P3) components. ERP–behavior correlations were examined across visibility levels. Results: No group differences were observed at the lowest visibility levels. Group differences emerged selectively at intermediate to high visibility levels, where athletes showed higher accuracy and a tendency toward faster responses. Drift–diffusion modeling revealed that this advantage was driven by higher drift rates in athletes, with no group differences in non-decision time, boundary separation, or starting point. Early ERP components (N2, P2) were strongly modulated by stimulus visibility but showed no consistent group differences. In contrast, the P3 component exhibited earlier and more pronounced differentiation across visibility levels in athletes. In the passive viewing task, group differences were substantially reduced. ERP–behavior analyses showed stronger and earlier P3–behavior coupling in athletes. Conclusions: Open-skill sports expertise selectively optimizes late-stage evidence accumulation and its translation into behavior, rather than enhancing unconscious or early sensory processing. Full article

Background/Objectives: From birth, infants learn how to interact with the world through exploration. It has been proposed that this early learning phase is driven by motor babbling: the spontaneous generation of exploratory movements that are progressively consolidated through associative mechanisms. This process leads to the acquisition of a repertoire of hand movements such as single- or multi-finger flexion, extension, touching, and pushing. Later, in a second phase, some of these movements (e.g., those that happen to enable access to biologically salient stimuli, such as grasping food) are further reinforced and consolidated through rewards obtained from the environment. However, the neural mechanisms underlying these processes remain unclear. Here, we used a fully neuroanatomically and neurophysiologically constrained neural network model to investigate the brain correlates of these processes. Methods: The model consists of six neural maps simulating six human brain areas, including three pre-central (motor-related) and three post-central (sensory-related) regions. Each map is composed of excitatory and inhibitory spiking neurons, with biologically constrained within- and between-area connectivity forming recurrent circuits. Hand action execution and corresponding haptic perception are simulated simply as activity in primary motor and somatosensory model areas, respectively. During an initial “exploratory” phase, the network learned, via Hebbian mechanisms, associations—as emerging distributed cell assembly (CA) circuits—linking “motor” to corresponding “haptic feedback” patterns. As a result of this initial training, the model began to exhibit spontaneous ignitions of these CA circuits, an emergent phenomenon taken to represent internally generated, non-stimulus-driven attempts at hand action exploitation. In a second phase, a global reward signal, simulating dopamine-mediated reward encoding, was applied to only a subset of “successful” actions upon their noise-driven ignition. Results: During the first exploratory phase, the neural architecture autonomously developed “action-perception” circuits corresponding to multiple possible hand actions. During the subsequent exploitation phase, positively reinforced circuits increased in size and, consequently, in frequency of spontaneous ignition, when compared to non-rewarded “actions”. Conclusions: These results provide a mechanistic account, at the cortical-circuit level, of the early acquisition of hand actions, of their subsequent consolidation, and of the spontaneous transition of an agent’s behavior from exploration to reward-seeking, as typically observed in humans and animals during development. Full article

With the increasing prominence of sustainable consumption and the rising influence of Generation Z in the fashion market, secondhand fashion e-commerce platforms have become essential carriers of green fashion. Although AI-assisted recommendation mechanisms are widely embedded in these platforms, their psychological and behavioral effects on users’ continuous use and social engagement remain insufficiently examined. To address this gap, this study incorporates the Stimulus–Organism–Response (SOR) framework to investigate the psychological reaction pathways and behavioral intentions of Generation Z users within Human-AI Collaboration-enabled green e-commerce environments. Three AI-driven service stimuli—Human-AI Collaborative Recommendation Perception, AI Interaction Transparency, and Perceived Personalization—were conceptualized as stimulus variables; Psychological Immersion, Emotional Triggering, Cognitive Engagement, and Platform Trust were modeled as organism variables; and Continuous Use Intention and Social Sharing Intention served as behavioral response variables. Based on 498 valid samples analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM), the results demonstrate strong empirical support for all proposed hypotheses. Specifically, AI-driven stimuli significantly and positively influence psychological responses, which subsequently strengthen users’ continuous usage and social sharing intentions. This research provides theoretical insights for developing Human-AI Collaboration-enabled service systems that balance efficiency and emotional resonance on green e-commerce platforms, and offers practical implications for promoting sustainable fashion values among younger consumers. Full article

Digital retail is undergoing a paradigm shift driven by the deep integration of artificial intelligence (AI) and augmented reality (AR). Although prior studies have examined the independent effects of AI-based personalized recommendation (cognitive path) and AR-enabled immersion (experiential path), how their integration systematically shapes user behavior through internal psychological mechanisms remains an important unresolved theoretical gap. To address this gap, this study develops an integrated model grounded in the stimulus–organism–response (S-O-R) framework and trust transfer theory. Specifically, the model examines how personalized recommendation, as a dynamic external stimulus, influences users’ cognitive state (perceived usefulness) and experiential state (immersion); how the overall trust of users in the integrated platform can be used as a key boundary condition to adjust the transformation efficiency from the above stimulus to the internal state; and how the above cognitive and experiential states can ultimately drive the continued usage intention through the mediation of positive emotional response. Based on survey data from 400 Chinese consumers with AR shopping experience on Taobao, analyzed using structural equation modeling (SEM), the results indicate that (1) personalized recommendation positively affects both immersion and perceived usefulness; (2) platform trust significantly and positively moderates the effects of personalized recommendation on both immersion and perceived usefulness; (3) both cognitive and experiential states stimulate positive emotions, which in turn enhance continued usage intention, with perceived usefulness exerting a stronger effect; (4) a key theoretical finding is that there is a significant positive correlation between perceived usefulness and immersion, revealing the coupling of psychological paths in an integrated environment; however, immersion does not moderate the effect of personalized recommendation on emotional responses, suggesting that the current integration mode emphasizes the formation of a stable psychological structure rather than real-time interaction. This study makes three contributions to the existing literature. First, it extends the application of S–O–R theory in a complex technological environment by analyzing the “organism” as a parallel and related cognitive-experience dual path and confirming its coupling relationship. Second, it elucidates the enabling role of trust as a moderating mechanism rather than a direct antecedent, thereby enriching micro-level evidence for trust transfer theory in the context of technology integration. Finally, by contrasting path coupling with process regulation, this study provides a more detailed distinction for understanding the theoretical connotations and boundaries of AI–AR technology integration, which may mainly be a kind of structural integration. Full article

Digital cultural-heritage (DCH) platforms are integral to achieving UN SDG Target 11.4, yet their long-term sustainability is compromised by a systemic vulnerability: the rapid decay of user engagement once the initial “novelty effect” fades. To address the theoretical anomaly of the “null effect” regarding value perception found in prior studies, this paper develops a competitive dual-path model to determine whether information-centric or experience-centric strategies effectively foster sustainable continuance intention. Drawing on the stimulus–organism–response (S-O-R) framework, interactivity is modelled as a high-order managerial investment. A quantitative survey of 407 DCH users was analysed using covariance-based structural equation modelling (CB-SEM). The results resolve the strategic dilemma: while interactivity enhances both pathways, a chi-square difference test $\left(\Delta {\chi }^2\left(1\right)=26.207\right.$, p < 0.001) confirms that affective value exerts a significantly stronger impact on cultural identity than epistemic value, supporting the affective primacy hypothesis. Crucially, cultural identity serves as the essential mediator that translates user experience into “emotional stickiness.” By demonstrating that narrative-driven affective engagement is superior to mere information dissemination, this study provides a validated blueprint for virtual–real symbiosis. The findings offer actionable guidance for managers to build digital resilience and safeguard heritage transmission across generations. Full article

Autoimmune flares are often accompanied by abrupt surges of circulating plasmablasts—short-lived, high-output antibody-secreting cells generated through extrafollicular B-cell activation in response to microbial cues. Three categories of microbial input appear to repeatedly trigger these “plasmablast storms”: latent herpesvirus reactivations (Epstein–Barr virus, cytomegalovirus, human herpesvirus-6, varicella–zoster virus), acute respiratory or gastrointestinal infections including SARS-CoV-2, and chronic oral or gut dysbiosis. Although biologically distinct, these stimuli converge on innate sensing pathways driven by pathogen-associated molecular patterns such as unmethylated CpG DNA, single-stranded RNA, lipopolysaccharide, and bacterial lipoglycans. Through Toll-like receptors and type I interferon signalling, microbial signatures accelerate class switching, amplify inflammatory cytokine milieus, and lower B-cell activation thresholds, enabling rapid plasmablast mobilisation. Dysbiosis further maintains B cells in a hyper-responsive state by disrupting mucosal homeostasis and altering microbial metabolite profiles, thereby reducing the stimulus required to trigger plasmablast bursts. Once generated, these waves of oligoclonal plasmablasts home to inflamed tissues, where chemokine and adhesion landscapes shape their retention during flares. Emerging evidence suggests that such episodic plasmablast expansions promote autoantibody diversification, somatic hypermutation, and epitope spreading, progressively eroding tolerance. This review synthesizes these insights into a unified model in which infections and dysbiosis promote microbe-licensed plasmablast storms that influence the tempo and severity of autoimmune disease. Full article

This study examines the psychological mechanisms underlying service stickiness during the mature phase of the AI subscription economy, with particular attention to the paradox of subscription fatigue. To enhance conceptual clarity, AI-driven stimuli—specifically Algorithmic Curation and Technological Fluidity—are defined as perceived attributes at the individual level. Employing the Stimulus–Organism–Response (S-O-R) framework, the research explores how these perceived stimuli influence consumers’ internal states (Cognitive Efficiency and Serendipity) and subsequent behavioral responses (Service Stickiness). Empirical analysis using partial least squares structural equation modeling (PLS-SEM) on data from U.S. subscription service users yields several theoretical insights. Cognitive Efficiency is identified as the primary driver of stickiness, indicating that, in the context of subscription fatigue, the utilitarian benefit of reduced cognitive effort surpasses hedonic enjoyment. Additionally, the study identifies a “Frictionless Trap,” in which excessive Technological Fluidity negatively affects Serendipity (β = −0.195), suggesting that an entirely seamless experience may create a filter bubble that limits unexpected discovery. As a result, Serendipity does not significantly affect stickiness in the aggregate model. However, post hoc analysis demonstrates that Serendipity remains significant for high-income users, while Cognitive Efficiency is most influential in high-frequency utilitarian contexts, such as food services. These findings indicate that sustainable retention depends on reducing cognitive load while intentionally introducing friction to preserve opportunities for discovery. Full article

Wardrobe fronts form a major visual element in bedroom interiors, yet material selection for their colors and textures often relies on intuition rather than evidence. This study develops a data-driven framework that links gaze behavior and affective responses to occupants’ preferences for wardrobe front materials. Forty adults evaluated color and texture swatches and rendered bedroom scenes while eye-tracking data capturing attraction, retention, and exploration were collected. Pairwise choices were modeled using a Bradley–Terry approach, and visual-attention features were integrated with emotion ratings to construct an interpretable attention index for predicting preferences. Results show that neutral light colors and structured wood-like textures consistently rank highest, with scene context reducing preference differences but not altering the order. Shorter time to first fixation and longer fixation duration were the strongest predictors of desirability, demonstrating the combined influence of rapid visual capture and sustained attention. Within the tested stimulus set and viewing conditions, the proposed pipeline yields consistent preference rankings and an interpretable attention-based score that supports evidence-informed shortlisting of wardrobe-front materials. The reported relationships between gaze, affect, and choice are associative and are intended to guide design decisions within the scope of the present experimental settings. Full article

The global issue of food waste is a significant concern due to its extensive social, economic, and environmental repercussions. To attain our sustainable future objectives, we must confront the food waste challenge directly. This study, grounded on the Stimulus–Organism–Response (S-O-R) theoretical framework, examines the impact of AI-based stimuli—passion, usability, perceived personalization, and perceived interactivity—on users’ intentions of minimizing food waste. Social presence and psychological engagement signify internal organism (O) states, while self-efficacy acts as the moderating factor between these organism states and intention (R). Data were gathered via Computer-Assisted Web Interviewing (CAWI) in a stratified quota sample of 315 participants in Lithuania, concentrating on Generation Y and Millennial Generation Z consumers of the Samsung Food app, aimed at promoting food waste reduction. Participants were pre-screened and recruited via several means to guarantee an adequate sample. The results indicate that passion, usability, and perceived interactivity substantially influence social presence and psychological engagement. Nonetheless, these organism-level variables did not have an immediate impact on behavioral intention, and all indirect (mediated) effects from stimulus response were significantly rejected. Conversely, self-efficacy considerably influenced the association between social presence and psychological engagement with intention, indicating that enhanced user confidence enhances the possibility of turning engagement into behavioral responses. This study features generational differences between Y and Z and only found significant interaction between perceived personalization and social presence in Generation Y, as compared to Generation Z. This work extends the literature on AI-driven behavior modification by asserting that mere involvement is inadequate. Enabling consumers by enhancing self-efficacy is crucial for developing viable AI-based applications that encourage sustainable customer behavior. Full article

This study develops a value co-creation-oriented analytical framework to evaluate the performance and evolutionary dynamics of China’s national-level quality policies from 1979 to 2023. A comprehensive categorization and scoring system is established to measure policy intensity, coordination, and comprehensiveness. Policy texts are systematically coded through content analysis, and indicator weights are determined using the Analytic Hierarchy Process (AHP). The resulting composite effect values are further analyzed through punctuated-equilibrium testing, breakpoint analysis, and a Vector Autoregression (VAR) model to estimate the temporal lag of policy implementation. Based on 10,962 policy documents retrieved from the Peking University Law Database, the results reveal clear evolutionary stages and cyclical upward trends in policy performance since the reform and opening-up, while the insufficient supply of demand-side policies remains a long-term structural weakness. The overall evolution path shows a transition from unilateral government provision centered on public value to dual government–market regulation driven by mixed commercial value, and finally toward pluralistic quality governance under value co-creation. Empirical evidence also indicates that quality policies act as short-term stimulus instruments that generate positive but sectorally differentiated effects across the three major industries. These findings highlight the need to expand policy coverage, enhance coordination and comprehensiveness, and rebalance the supply structure. Strengthening short-term stimulus effects while promoting inclusive, co-governed, and sustainable quality policy systems can further improve long-term effectiveness and provide useful insights for international discussions on value co-creation-based governance. Full article

Exercise acts as a physiological stimulus, requiring precise coordination among endocrine, microbial, and mitochondrial systems to maintain metabolic stability through allostatic regulation. The goal of the article is to integrate multidisciplinary evidence to characterize the thyroid–microbiome–mitochondrial axis as a key regulator of the allostatic state in athletic physiological response. During acute, chronic, and overload training phases, the thyroid–microbiome–mitochondrial axis operates bidirectionally, coupling microbial signaling with endocrine and mitochondrial networks to mediate metabolic response to exercise. This response shows interindividual variability driven by sex, age, genetics, and nutritional status, shaping the boundaries between adaptive efficiency and allostatic overload. Microbial metabolites, such as short-chain fatty acids (SCFA) and secondary bile acids, modulate deiodinase activity, bile acid recycling, and mitochondrial biogenesis through AMPK–SIRT1–PGC1α signaling, optimizing substrate use and thermogenic capacity. Thyroid hormones reciprocally regulate gut motility, luminal pH, and bile secretion, maintaining microbial diversity and mineral absorption. Under excessive training load, caloric restriction, or inadequate recovery, this network becomes transiently unbalanced: SCFA synthesis decreases, D3 activity increases, and a reversible low-T₃/high-rT₃ pattern emerges, resembling early Hashimoto- or Graves-like responses. Selenium-, zinc-, and iron-dependent enzymes form the redox link between microbial metabolism, thyroid control, and mitochondrial defense. In conclusion, the thyroid–microbiome–mitochondrial axis provides the physiological basis for the allostatic state, a reversible phase of dynamic recalibration that integrates training, nutrition, environmental stress, and circadian cues to sustain thyroid activity, mitochondrial efficiency, and microbial balance. This integrative perspective supports precision interventions to optimize recovery and performance in athletes. Full article

Background/Objectives: Advanced drug delivery systems (DDSs) are essential for targeted delivery, controlled release, and reduced systemic toxicity, but their clinical adoption is limited by biological barriers, manufacturing complexities, and cost. The aim of this systematic review is to critically evaluate the quantitative relationships between platform design, overcoming biological barriers, and clinical translation outcomes for DDS developed between 2016 and 2025. Methods: A comprehensive literature search was conducted in PubMed/MEDLINE, Scopus, and Web of Science (January 2016–April 2025) in accordance with the PRISMA 2020 guidelines. Included studies focused on experimental or clinical data for nanocarrier platforms (liposomes, lipid nanoparticles, polymer systems, biomimetic carriers, extracellular vesicles). Data on platform characteristics, interactions with barriers, pharmacokinetics, manufacturing, and clinical outcomes were extracted and synthesized in narrative form due to the significant methodological heterogeneity. Results: An analysis of 77 included studies confirms that successful clinical translation depends on matching the physicochemical properties of the carrier (size, surface chemistry, material) to specific biological barriers. Liposomes and lipid nanoparticles (LNPs) remain the most clinically validated platforms, exploiting the EPR effect and liver tropism, respectively. Key engineering solutions include stealth coatings, ligand-mediated targeting, and stimulus-responsive materials to overcome barriers such as mononuclear phagocyte system clearance, the blood–brain barrier, and mucosal barriers. Microfluidic and continuous manufacturing processes enable reproducibility, but scalability, cost, and immunogenicity (e.g., anti-PEG responses) remain key translational challenges. Engineered extracellular vesicles, biomimetic carriers, and 3D/4D-printed systems combined with AI-driven design demonstrate the potential for personalized, adaptive delivery. Conclusions: Cutting-edge DDSs have validated their clinical value, but realizing their full potential requires a holistic, patient-centered design approach integrating barrier-specific engineering, scalable manufacturing, and rigorous safety assessment from the earliest stages of development. Further progress will depend on standardizing methods for new platforms (e.g., extracellular vesicles), implementing digital and AI tools, and ensuring translational feasibility as a fundamental principle. Full article

Real estate inventory dynamics exhibit distinct temporal patterns and spatial heterogeneity, and precise identification of these trends serves as a prerequisite for effective policy formulation. Research on the spatiotemporal evolution patterns and influencing factors of real estate inventory holds significant academic and practical value. By employing ESDA, the Boston Matrix, and geographically weighted regression models to analyze 2017–2022 data from 287 Chinese cities, this study reveals a cyclical shift in China’s real estate inventory management—from “destocking” to “restocking”. The underlying drivers have transitioned from policy-led interventions to fundamentals-driven factors, including population dynamics, income levels, and market expectations. China’s real estate inventory and its changes exhibit significant spatiotemporal differentiation and spatial agglomeration patterns, demonstrating a spatial structure characterized by “multiple clustered highlands with peripheral lowlands” led by urban agglomerations. The influencing mechanism of China’s real estate inventory constitutes a complex system shaped by three key dimensions: macro-level drivers, regional differentiation, and structural contradictions. Policymakers should reorient destocking policies from “short-term stimulus” to “long-term coordination”, from “industrial policy” to “spatial policy”, and from addressing market “symptoms” to tackling “root causes”. This study argues that effective destocking policies constitute a systematic engineering challenge, demanding policymakers demonstrate profound analytical depth. They must move beyond simplistic sales metrics and perform multi-dimensional evaluations encompassing economic geography, demographic trends, fiscal systems, and land supply mechanisms. This paradigm shift from “symptom management” to “root cause resolution” and “systemic regulation” is essential for achieving sustainable real estate market development. Full article

Physical exercise is a potent non-pharmacological strategy for the prevention and management of chronic non-communicable diseases (NCDs), including type 2 diabetes, cardiovascular diseases, obesity, and certain cancers. Growing evidence demonstrates that the benefits of exercise extend beyond its physiological effects and are largely mediated by coordinated molecular and cellular adaptations. This review synthesizes current knowledge on the key mechanisms through which exercise modulates metabolic health, emphasizing intracellular signaling pathways, epigenetic regulation, and myokine-driven inter-organ communication. Exercise induces acute and chronic activation of pathways such as AMPK, PGC-1α, mTOR, MAPKs, and NF-κB, leading to enhanced mitochondrial biogenesis, improved oxidative capacity, refined energy sensing, and reduced inflammation. Additionally, repeated muscle contraction stimulates the release of myokines—including IL-6, irisin, BDNF, FGF21, apelin, and others—that act through endocrine and paracrine routes to regulate glucose and lipid metabolism, insulin secretion, adipose tissue remodeling, neuroplasticity, and systemic inflammatory tone. Epigenetic modifications and exercise-responsive microRNAs further contribute to long-term metabolic reprogramming. Collectively, these molecular adaptations establish exercise as a systemic biological stimulus capable of restoring metabolic homeostasis and counteracting the pathophysiological processes underlying NCDs. Understanding these mechanisms provides a foundation for developing targeted, personalized exercise-based interventions in preventive and therapeutic medicine. Full article