Search Results (334)

Existing research confirms associations between Big Five personality traits and emotional states, yet investigations into how personality traits modulate emotional dynamics and their gender-specific patterns remain limited. The present study developed a TFace-Bi-GRU-SE deep learning model that achieved a weighted accuracy of 63.50 ± 0.98% (peak single-run: 64.96%) and an F1 score of 65.21% in performance testing, with a single-inference time of 14.1 s, outperforming traditional methods. The model processed 10 min video recordings from 30 participants (19,262 observations), generating time-series data for valence (P) and arousal (A). Combined with Big Five personality assessments, continuous-time structural equation modeling (CTSEM) revealed distinct emotional dynamics: both P and A exhibited significant negative autoregression (−0.056 and −0.558, p < 0.001), with A reverting to baseline substantially faster (half-life: 1.2 s) than P (half-life: 12.3 s); cross-lagged effects were nonsignificant (P_A: 0.007; A_P: −0.026, p > 0.05). Arousal demonstrated greater instantaneous volatility (=0.339) than valence (=0.286, p < 0.001), with positive covariation between dimensions (0.218, p = 0.006). Exploratory analyses (N = 30) indicated that higher neuroticism and openness scores were associated with elevated arousal (Cohen’s d > 0.8), whereas higher agreeableness and conscientiousness scores were associated with elevated valence (d > 0.8). Gender moderated the neuroticism–arousal relationship, with more potent effects in females (r = 0.746, p = 0.008). Robustness analyses demonstrated high stability of core DRIFT parameters (P_P, A_A): bootstrap resampling (n = 50) yielded coefficients of variation < 0.35 with 100% directional consistency; subgroup validation confirmed cross-sample invariance. Sensitivity analyses revealed that an additional 8% measurement error induced less than 9% bias (8.3% for both P_P and A_A) in autoregressive parameters while preserving half-life ratios, confirming CTSEM’s capacity to extract reliable dynamics from moderately accurate AI outputs. Bootstrap and Bayesian analyses identified ten personality–DRIFT associations with directional consistency ≥ 70%; these constitute preliminary hypotheses for adequately powered future studies (N ≥ 61). This study provides methodological foundations for personalized affective intervention research. Data and code are publicly available (see Data Availability Statement). Full article

Urban mental health is increasingly influenced by daily environmental exposures, yet limited empirical evidence exists regarding how the spatial configuration of blue–green environments, rather than their mere quantity, relates to emotional behavior in high-density cities. Guided by restoration theories and a perception-based perspective on landscape integration, this study analyzes the urban core of Shanghai by linking blue–green configurations to emotional states inferred from 20,907 geotagged social media facial photographs. Facial expressions serve to derive indices for emotional valence and arousal. The results demonstrate significant spatial clustering of emotional behavior, where hotspots are concentrated in higher-quality and more open settings, while coldspots cluster in dense areas with sparse vegetation. Emotional behavior also exhibits demographic heterogeneity, as females display higher valence and arousal than males. Furthermore, happiness tends to increase with age across both genders, whereas arousal declines specifically among male age groups. Crucially, emotional outcomes align more consistently with landscape integration and configuration than with isolated blue or green areas. Factors such as high connectivity, superior vegetation condition, and configurations featuring water embedded within green space are associated with favorable emotional responses. Conversely, extensive edge-dominated interfaces and high traffic exposure correlate with less favorable outcomes. These findings suggest a shift in blue–green planning from increasing total area toward optimizing spatial composition. Specifically, priority should be given to embedded and cohesive designs alongside the reduction of ambient stressors to foster emotionally supportive environments in dense urban cores. Methodologically, image-derived behavioral traces provide a scalable and ecologically grounded approach for investigating place-based affect at a city scale. Full article

Background: Although pneumococcal conjugate vaccines (PCVs) have substantially reduced invasive pneumococcal disease, the emergence of non-vaccine serotypes and antimicrobial-resistant strains has driven the development of higher-valency vaccines. To support functional immune evaluation of these vaccines, we developed and validated a sixplexed opsonophagocytic killing assay (OPA) covering 24 pneumococcal serotypes. Methods: Eight additional serotypes, beyond the 16 included in the conventional fourplex OPA, were generated through stepwise natural mutation under increasing concentrations of ciprofloxacin or doxycycline. Assay conditions were optimized by evaluating multiple effector-to-target (E:T) ratios and baby rabbit complement (BRC) concentrations to minimize non-specific killing (NSK). Validation assessed (1) specificity using inhibition OPA with homologous and heterologous polysaccharides, (2) accuracy by comparison with the single-serotype OPA (SOPA), and (3) precision across five independent experiments using the coefficient of variation (CV). Results: An E:T ratio of 200:1 combined with 10% BRC consistently maintained NSK below 30% across all assay sets. High serotype specificity was demonstrated by near-complete inhibition following homologous polysaccharide adsorption for all serotypes except serotypes 4 and 8, which exhibited very low opsonic indices. Results from the sixplexed OPA showed strong concordance with SOPA, and overall assay precision was acceptable, with CVs generally below 30% when serotypes with very low opsonic activity were excluded. Conclusions: The sixplexed OPA expands functional antibody assessment from 16 to 24 serotypes within four assay sets, providing an efficient and scalable platform for immunogenicity evaluation of current and next-generation high-valency pneumococcal vaccines. Full article

Color metaphors may shape how people mentally represent abstract legal values such as justice and thereby influence legal socialization and law-related cognition. We tested whether black/white color terms are metaphorically linked to justice conceived specifically as a legal value, and whether these linkages vary with task demands. In two preregistered experiments that controlled for affective valence, word frequency, and semantic relatedness, Experiment 1 employed a Stroop-style lexical-judgment task with law-relevant terms and found faster responses to justice-related (legal) words than to injustice-related words and higher accuracy for white-colored stimuli, but no reliable color × meaning interaction—suggesting the absence of an automatic color–justice congruency effect during early, automatic processing. Experiment 2 used a translation-matching paradigm in which participants selected black or white translations for unfamiliar foreign words; here, participants systematically matched justice-related (legal) items with white and injustice-related items with black at rates above chance, revealing explicit color–justice associations. Together, the results point to a robust mental linkage of white with justice as a legal value, while black–injustice mappings emerge primarily under explicit selection demands. These findings suggest that black/white color metaphors organize law-related moral cognition but are flexibly activated depending on cognitive task and processing level. Full article

Facial expression recognition (FER) in naturalistic settings is constrained by label ambiguity and variability in stimulus–response alignment. Adopting a data-centric perspective, this study examined whether emotional intelligence (EI)-stratified training data influence FER performance by treating EI as a qualitative factor associated with affective data consistency. Naturally elicited facial expressions were collected in a controlled emotion induction experiment with subjective arousal and valence ratings. Using response-driven labeling, neutral ratings were retained as indicators of ambiguity. Participants were grouped into High and Low EI based on the alignment between subjective evaluations and outputs from a pretrained affect estimator. Identical binary classifiers for arousal and valence recognition were trained while varying only the training data composition and evaluated across baseline, unambiguous, and ambiguous test sets using independent training repetitions with repetition-level statistical aggregation. EI-stratified training was associated with statistically detectable, context-dependent performance differences: group effects were observed primarily under baseline conditions and, to a lesser extent, under ambiguous conditions, whereas no reliable differences emerged under unambiguous conditions. Pooled discrimination differences were modest, but item-level analyses identified significant differences in classification correctness in specific task–condition combinations. Comparable patterns were observed across alternative backbone architectures. These findings indicate that FER performance in naturalistic contexts is influenced not only by model architecture but also by the statistical structure and internal coherence of the training data, supporting EI-informed data selection in ambiguity-prone scenarios. Full article

In the post-Moore’s Law era, conventional Von Neumann architectures face critical limitations, such as the “memory wall” and excessive power consumption, particularly when processing unstructured data. Neuromorphic computing, inspired by the human brain, offers a promising solution through parallel processing and adaptive learning. Among the candidates for artificial synapses, memristors based on two-dimensional MXenes (specifically Ti₃C₂T_x) have attracted significant attention due to their unique layered structure, high metallic conductivity, and tunable physicochemical properties. This review provides a comprehensive analysis of MXene-based memristors, from material synthesis to system-level applications. We examine how different synthesis strategies, including etching methods, directly influence device performance and elucidate the underlying resistive switching mechanisms driven by ion migration, valence change, and interfacial processes. Furthermore, the review demonstrates the efficacy of MXenes in emulating biological synaptic functions—such as spike-timing-dependent plasticity (STDP) and long-term potentiation/depression (LTP/LTD)—and their application in tasks like handwritten digit recognition. Finally, we highlight emerging frontiers in flexible electronics and in-sensor computing, offering insights into the future trajectory of integrated sensing, memory, and computation. Full article

With the increasing deployment of lithium iron phosphate (LiFePO₄) batteries in electric vehicles and energy storage systems, the recycling of these materials has become an urgent necessity. Specifically, the reclamation of lithium iron phosphate cathode materials presents a significant challenge in the recycling process. In this study, we proposed an efficient low-temperature hydrothermal direct regeneration method aimed at repairing lithium vacancies and Fe/Li inversion defects in spent lithium iron phosphate resulting from prolonged cycling. By using this method, spent lithium iron phosphate was successfully regenerated through a hydrothermal process conducted at 80 °C for 6 h, utilizing hydrazine hydrate (N₂H₄·H₂O) as a potent reducing agent and lithium hydroxide (LiOH·H₂O) as the lithium source. X-ray diffraction (XRD) analysis, coupled with Rietveld refinement, revealed a substantial reduction in the concentration of Fe/Li anti-site defects in the spent material, decreasing from 8.8% to 3.3% following regeneration. Consequently, the electrochemical performance was significantly restored. The initial specific discharge capacity increased from 118.0 mAh·g⁻¹ to 150.3 mAh·g⁻¹, and the capacity retention after 100 cycles (at 1 C) improved from 67.5% to 90.7%. The hydrothermal regeneration process introduced in this work effectively repairs the material structure and restores the active valence state of iron, thereby significantly enhancing lithium-ion diffusion and electron transport capabilities. This approach constitutes a technically viable solution for the efficient, environmentally friendly, and cost-effective recycling of spent lithium-ion batteries. Full article

A targeted modification approach involving the synthesis of Ce/C co-doped TiO₂ aerogels (CeCTi) via a sol–gel method combined with supercritical CO₂ drying and subsequent heat treatment is employed to enhance the photocatalytic CO₂ reduction performance of cost-effective and stable TiO₂ aerogels. The results demonstrate that the CeCTi exhibits a pearl-like porous network structure, an optical band gap of 2.90 eV, and a maximum specific surface area of 188.81 m²/g. The black aerogel sample shows an enhanced light absorption capability resulting from the Ce/C co-doping, which is attributed to the formation of oxygen vacancies. Under simulated sunlight irradiation, the production rates of CH₄ and CO reach 27.06 and 97.11 μmol g⁻¹ h⁻¹ without any co-catalysts or sacrificial agents, respectively, which are 82.0 and 5.7 times higher than those of the pristine TiO₂ aerogel. DFT reveals that C-doping facilitates the formation of oxygen vacancies, which introduces defect states within the calculational band gap of TiO₂. The proposed photocatalytic mechanism involves the light-induced excitation of electrons from the valence band to the conduction band, their trapping by oxygen vacancies to prolong the charge carrier lifetime, and their subsequent transfer to adsorbed CO₂ molecules, thereby enabling efficient CO₂ reduction, which is experimentally supported by photoluminescence measurements. Full article

The regulation of sensory processing by centralized neuromodulatory systems can alter behavioral responses to social cues. Neuromodulatory systems such as the serotonergic neurons in the dorsal raphé nucleus (DRN) show heterogenous responses to different types of sensory stimuli or to stimulus qualities such as reward, valence, or salience. Sensory neuromodulation could therefore be related to a broader quality of the behavioral context or to specific types of social cues. We assessed this issue by presenting male mice with either playback of female vocal signals associated with defensive aggression (squeaks) or silence, and the presence or absence of a female. Activity in regions of the DRN that project to the auditory midbrain was assessed through co-labeling with antibodies to the serotonin synthetic enzyme tryptophan hydroxylase (TPH) and the immediate early gene product c-Fos. Female presence or absence had the largest effect, decreasing the co-localization of TPH and c-Fos, while the playback of squeaks had effects that were condition-dependent, increasing co-label only when females were absent. Squeak playback further decreased the correlation in the numbers of co-labeled neurons between two dorsal subdivisions of the DRN, the DRD and DRL. These results are inconsistent with an auditory-exclusive feedback loop. Instead, cues associated with female presence heavily influence raphé activity, with squeaks playing a modifying and context-dependent role. Because the elevation of serotonin in the IC causes males to become more responsive to female squeaks, these findings suggest that a nuanced interaction of positive and negative cues during social interaction may fine-tune male responses to the vocalization of social partners, in part through the serotonergic system. Full article

Potato starch offers the unique potential of mineral enrichment through the presence of phosphorylated amylopectin chains. This property was utilised in a straightforward dual modification of native potato starch by combining mineral enrichment with dry heat treatments (DHT). DHT itself (110–130 °C, 3–6% moisture, 2 h) affords potato starches with lower viscosity and gelatinisation temperatures and higher contents of digestible starch. Prior ion exchange with Na⁺, K⁺, Mg²⁺, and Ca²⁺ enhanced the versatility of dry heat treatments. This study demonstrates the fine-tuning of functional properties (rheology) of these novel, dual-modified starches. Of special interest are magnesium and calcium due to their nutritional value and their valency, allowing ionic cross-linking. The present study contributes to the understanding of starch–ion interactions in DHT, clearly highlighting the role of specific ion effects, as per the Hofmeister series (K⁺ > Na⁺ and Ca²⁺ > Mg²⁺), in addition to the reversible ionic cross-linking effect of divalent cations. This knowledge is of use for potential substitution of chemically modified starches in food products, serving relevant trends and needs of today’s food industry for clean-label starches. Full article

Background/Objectives: NANOBODY^® molecules (VHHs) are attractive vectors for radiopharmaceuticals due to their small size and high target affinity, but rapid clearance and pronounced kidney retention limit their therapeutic applicability. Binding to serum albumin is a widely used strategy to prolong circulation, yet the respective contributions of albumin-binding affinity and molecular format remain insufficiently defined. This study aimed to systematically evaluate how affinity and valency modulate VHH pharmacokinetics. Methods: Four monovalent albumin-binding VHHs spanning nanomolar to micromolar affinities and two bivalent constructs were engineered, generated by fusing an albumin-binding VHH to an irrelevant non-binding VHH. All constructs incorporated a site-specific cysteine for DFO* conjugation, enabling uniform zirconium-89 labeling with high radiochemical purity. Pharmacokinetics were assessed in healthy mice using serial blood sampling and positron emission tomography. Blood and kidney exposure were quantified by non-compartmental analysis. Results: All albumin-binding constructs showed increased systemic exposure and reduced kidney uptake relative to a non-binding control. Nanomolar-affinity binders reached maximal exposure, and further affinity increases (K_D < ~100 nM) did not improve pharmacokinetics, suggesting a threshold. The micromolar binder showed intermediate exposure but still reduced renal retention compared with control. Valency effects were affinity-dependent. They were negligible at high affinity but pronounced at low affinity, where bivalency reduced systemic exposure and increased kidney uptake toward control levels. Conclusions: Albumin binding enables tuning of VHH pharmacokinetics in an affinity-dependent manner. Above an apparent affinity threshold, pharmacokinetics become format independent, whereas below this threshold, molecular format substantially influences systemic and renal disposition. Full article

Background/Objectives: Wearable affective human–computer interaction increasingly relies on sparse-channel EEG signals to ensure comfort and practicality in real-life scenarios. However, the limited information provided by sparse-channel EEG, together with pronounced inter-subject variability, makes reliable cross-subject emotion recognition particularly challenging. Methods: To address these challenges, we propose a cross-subject emotion recognition model, termed TSCL-LwF, based on sparse-channel EEG. It combines a multi-scale convolutional network (TSCL) and an incremental learning strategy with Learning without Forgetting (LwF). Specifically, the TSCL is utilized to capture the spatio-temporal characteristics of sparse-channel EEG, which employs diverse receptive fields of convolutional networks to extract and fuse the interaction information within the local prefrontal area. The incremental learning strategy with LwF introduces a limited set of labeled target domain data and incorporates the knowledge distillation loss to retain the source domain knowledge while enabling rapid target domain adaptation. Results: Experiments on the DEAP dataset show that the proposed TSCL-LwF achieves accuracy of 77.26% for valence classification and 80.12% for arousal classification. Moreover, it also exhibits superior accuracy when evaluated on the self-collected dataset EPPVR. Conclusions: The successful implementation of cross-subject emotion recognition based on a sparse-channel EEG will facilitate the development of wearable EEG technologies with practical applications. Full article

This essay provides a neurobiological and neuroanatomical analysis of how the recently published Walla Emotion Model, with its neurobiologically grounded definitions, elucidates the evolutionary origin of affective processing from the sense of olfaction. The analysis first deconstructs the model’s hierarchical framework, which distinguishes between rapid, non-conscious affective processing (neural activity coding for valence of stimuli), conscious, subjective feelings, and observable, communicative emotions. It then details the unique neuroanatomical pathway of the olfactory system, highlighting its most direct, subcortical connections to the limbic system (only two synapses) (shared subcortical network between olfaction and affection). The core argument presented is that this emotion model’s definition of affective processing as being distinct from an emotion is a direct conceptual reflection of the ancient, hardwired, and survival-oriented function of olfaction. This link is substantiated by empirical evidence from studies on sniffing behavior, startle reflex modulation, and non-conscious physiological responses, all of which provide empirical evidence for a non-conscious, non-cognitive evaluation of olfactory stimuli. First, this essay concludes that a clear distinction between affective processing, feelings, and emotions offers a coherent framework that has the potential to resolve long-standing terminological ambiguities in the affective science. Second, it also aims at providing a paradigm for understanding the foundational role of a specific sensory modality in the evolution of our most primitive and yet so evident and impactful affective responses serving the adaptation of produced behavior in humans. Finally, some ideas for broader implications are mentioned. Full article

This study investigates the influence of three biophilic interior design variables: natural light, interior vegetation (vertical green wall), and biomorphic form (biomorphic wall panel) on affective and physiological responses in a design studio interior utilizing immersive virtual reality (IVR) and wearable biofeedback technology. This study was a within-participant 2³ factorial design that included one baseline and eight IVR studio conditions. Participants experienced all conditions while reporting affects using the Self-Assessment Manikin (SAM) valence and arousal scales, electrodermal activity (EDA), and skin temperature (ST). Cybersickness was measured with the Simulator Sickness Questionnaire (SSQ) and presence was assessed using the Igroup Presence Questionnaire and Slater-Usoh-Steed presence measures (IPQ, SUS), while baseline anxiety (STAI) was controlled. The results demonstrated a significant primary influence of natural light on SAM valence ratings: conditions with natural light were evaluated as more pleasant than the non-variable and baseline condition, whereas interior vegetation and biomorphic form had smaller, context-dependent effects that were most evident when layered with natural light. Differences in SAM arousal ratings were modest and non-systematic. EDA did not differentiate, and ST showed only small shifts, indicating that during calm exploratory monitoring, subjective affect was more responsive. The circumplex findings guided to an activity-specific zoned interior rather than a single uniform design studio. Full article

The role of the metal valence state on the surface properties of metal-loaded clay minerals in the adsorption/oxidative degradation of an antibiotic was investigated. Transitional metal cations and their zero-valent counterparts such as Fe⁰, Ni⁰, Co⁰ and Cu⁰ supported on montmorillonite were comparatively investigated for their interactions during adsorption and toxicity tests of antibiotic norfloxacin (NOF). UV-Vis spectrophotometric and Fourier transform infrared (FTIR) spectroscopic analyses confirmed the involvement of the hydroxyl and carboxyl groups and/or piperazinyl nitrogen of NOF in the complexation with metal cations. Ecotoxicological assessment using aquatic plants Lemna minor showed that the metal cations reduce the bioavailability of the organic pollutant and that the zero-valent metals display higher toxicity due to their specific interaction with NOF and clay mineral surface. This evaluation will provide insights into potential environmental impacts of the co-occurrence of antibiotics and metals and will certainly contribute to correlating the safety of the water treatment by assessing the residual toxicity and its fluctuations. Full article