Search Results (4,989)

Effective implementation of silvopastoralism, a key Nature-Based Solution for Europe’s climate goals, is hindered by a lack of decision-support tools clarifying trade-offs between efficiency and extent of carbon sequestration. To address this, we developed a multi-objective scenario analysis (4064 scenarios) to identify optimal strategies for silvopastoral expansion across the EU27 Mediterranean bioregion. We found an inverse relationship defining a clear trade-off: scenarios achieving the highest mean sequestration (up to 2.5 Mg CO₂ ha⁻¹ year⁻¹) are spatially limited, whereas those maximising total gains (approaching 10⁷ Mg CO₂ year⁻¹ in total) do so by incorporating vast areas, lowering mean rates. This trade-off is formalised by a Pareto front, from which we defined a best-balanced optimal scenario and three policy regimes (conservative, balanced, expansive). Progressing across the front involved shifting from converting primarily shrubby and sparsely vegetated lands to incorporating grasslands and mixed agro-systems. At the NUTS2 level, Spain and Greece emerged as hotspots. Notably, converting arable land was not a primary contributor to carbon gains, as the marginal carbon benefit on these productive soils is lower than on marginal lands due to their higher baseline soil carbon levels, indicating that large-scale implementation can focus on marginal lands to avoid conflicts with food security. While subject to uncertainties of the underlying land-use and carbon models, this analysis demonstrates that our framework enables policymakers to select spatially explicit strategies aligned with specific budget or sequestration goals. These insights can inform CAP eco-schemes and national LULUCF strategies. The resulting maps and code are freely available. Full article

Objectives: This study aimed to assess stroke coordination and biomechanics in elite U23 male kayakers under valid on-water conditions (instrumented K1 kayak on a competition lake) across race-relevant stroke frequencies (60, 80, and 100 strokes·min⁻¹). Methods: To achieve our aims, twelve male athletes (age 21.00 ± 0.47 years) completed 500 m trials at three randomized paddle frequencies (60, 80, 100 strokes·min⁻¹) with 10 min of passive recovery in-between. Data were collected with inertial measurement units, and a customized seat/footrest with integrated strain-gauge sensors. Results: Principal Component Analysis identified four key components: Mechanical Work, Mechanical Energy, Stroke Variability (PCI, Phase Coordination Index), and boat acceleration, accounting for 76% of total variance. Linear mixed-effects models (within-subject LME; Participant random intercept; Satterthwaite df) revealed that Mechanical Work (χ² = 17.10, p < 0.001) and Mechanical Energy (χ² = 53.10, p < 0.001) increased significantly with stroke frequency. Phase Coordination Index showed a significant increase at 60 and 100 strokes·min⁻¹ (χ² = 16.78, p < 0.001; t = 4.78, p < 0.001), while boat acceleration was not significantly affected (χ² = 4.95, p = 0.08). The PCI correlated negatively with Mechanical Work (r = −0.37, p = 0.022) and positively with boat acceleration (r = 0.39, p = 0.010). Effect sizes were moderate to large (ηp² = 0.18–0.36; corresponding 95% confidence intervals are reported in the main text). For the primary mechanical indicator (Paddle Factor), the mixed-effects model yielded a marginal R² = 0.57, reflecting the proportion of variance explained by cadence. Conclusions: Approximately 80 strokes·min⁻¹ may represent a condition in which coordination metrics appear comparatively favorable. These findings are exploratory and hypothesis-generating, not prescriptive. No causal inference can be drawn, and any training application attempts should await replication in larger, longitudinal and randomized studies. Full article

Background/Objectives: Osteoarthritis (OA) remains a global health problem, as it can cause permanent joint damage, leading to irreversible disability. Therefore, there is a need for accessible and non-invasive alternative examinations, such as USG, serum COMP, and 25-hydroxyvitamin D [25(OH)D] assessment. This study aims to analyze the correlation between serum COMP and 25(OH)D levels and the degree of articular cartilage degradation in patients with knee OA, based on findings from USG and MRI examinations. Methods: A cross-sectional analytical study was conducted at Mohammad Hoesin Hospital, Palembang, from December 2024 to August 2025. 31 patients diagnosed with knee OA based on the 1990 American College of Rheumatology (ACR) classification criteria were enrolled. Serum COMP and 25(OH)D levels were measured. All patients underwent standardized USG and MRI examinations of the knee. Spearman’s rank correlation coefficient was used for statistical analysis. Results: The majority of the study subjects were female, comprising 23 (74.2%). The mean age was 63.90 ± 7.77 years with a body mass index of 25.46 ± 5.51 kg/m². Most subjects were engaged in heavy physical activity 17 (54.8%). Laboratory examination showed serum COMP levels with a median of 869 ng/mL and a range of 136–3302 ng/mL. Meanwhile, the 25(OH)D level demonstrated a mean value of 24.84 ± 7.33 ng/mL. The analysis revealed a strong and statistically significant positive correlation between serum COMP levels and the degree of articular cartilage degradation in knee OA. This correlation was observed in both USG (r = 0.61; p < 0.001) and MRI assessments (r = 0.72; p < 0.001). In contrast, serum 25(OH)D levels showed no significant correlation with cartilage degradation. The correlation coefficient between 25(OH)D levels and USG-assessed cartilage degradation was r = −0.12 (p = 0.51), and for MRI assessment, it was r = 0.17 (p = 0.92). Conclusions: A strong and significant positive correlation exists between serum COMP levels and the degree of articular cartilage degradation based on USG (r = 0.61; p < 0.001) and MRI (r = 0.72; p < 0.001). In contrast, serum 25(OH)D levels showed no significant correlation with cartilage degradation, implying that 25(OH)D may not directly reflect the extent of structural cartilage damage in knee osteoarthritis. This finding proves that an increase in serum COMP levels is associated with an increase in the degree of articular cartilage degradation in knee OA as measured by both USG and MRI. Full article

Background and Objectives: Interventions targeting the gut–brain axis offer potential for mitigating Subjective Cognitive Decline (SCD), a critical window for Alzheimer’s prevention. This study evaluated the effects of a novel probiotic supplement, ExoBDNF, on cognitive function, sleep, and emotional distress in adults with SCD. Materials and Methods: In this 9-week open-label study, participants received ExoBDNF supplementation. Efficacy was assessed using the SCD-Questionnaire (SCD-Q), DASS-21, PSQI, MoCA, and a computerized cognitive battery measuring inhibition (Go/No-Go), flexibility (Task Switching), and working memory. Results: Post-intervention analyses revealed significant improvements in subjective cognition (SCD-Q, p < 0.001), sleep quality (PSQI, p < 0.001), and emotional distress (DASS-21, p < 0.001). Objective cognitive performance also improved, with significant gains in MoCA scores (p = 0.047) and executive function metrics. Spearman correlation analysis indicated a significant link between cognitive and emotional changes: longitudinal reductions in SCD scores correlated with concurrent reductions in emotional distress (rho = 0.471, p = 0.009). Furthermore, higher baseline SCD scores predicted greater improvement in emotional outcomes (rho = −0.540, p = 0.002). Conclusions: ExoBDNF supplementation significantly enhanced cognitive performance, sleep quality, and emotional well-being. The findings demonstrate that improvements in subjective cognition are closely tied to alleviated emotional distress, supporting the gut–brain axis as a viable therapeutic target for early-stage cognitive decline. Full article

The color design of architectural interior display spaces directly affects the effectiveness of cultural information communication and the visual cognitive experience of viewers. However, there is currently a lack of combined subjective and objective evaluation regarding how to scientifically translate and apply traditional color systems in modern contexts. This study takes the virtual display space of traditional Chinese floral arrangements as a case, aiming to construct an evaluation framework integrating the Semantic Differential Method and eye-tracking technology, to empirically examine how color schemes based on the translation of traditional aesthetics affect the subjective perception and objective visual attention behavior of modern viewers. Firstly, colors were extracted and translated from Song Dynasty paintings and literature, constructing five sets of culturally representative color combination samples, which were then applied to standardized virtual exhibition booths. Eye tracking data of 49 participants during free viewing were recorded via an eye-tracker, and their subjective ratings on four dimensions—cultural color atmosphere perception, color matching comfort level, artwork form clarity, and explanatory text clarity—were collected. Data analysis comprehensively employed linear mixed models, non-parametric tests, and Spearman’s rank correlation analysis. The results show that, regarding subjective perception, different color schemes exhibited significant differences in traditional feel, comfort, and text clarity, with Sample 4 and Sample 5 performing better on multiple indicators; a moderate-strength, significant positive correlation was found between traditional cultural atmosphere perception and color matching comfort. Regarding objective eye-tracking behavior, color significantly influenced the overall visual engagement duration and the processing depth of the text area. Among them, the color scheme of Sample 5 better promoted sustained reading of auxiliary textual information, while the total fixation duration obtained for Sample 4 was significantly shorter than that of other schemes. No direct correlation was found between subjective ratings and spontaneous eye-tracking behavior under the experimental conditions of this study; the depth of processing textual information was a key factor driving overall visual engagement. The research provides empirical evidence and design insights for the scientific application of color in spaces such as cultural heritage displays to optimize visual experience. Full article

Background: Rosacea is a chronic facial skin disease in which persistent erythema is a significant clinical problem, often resistant to standard therapies. Intensive pulsating light (IPL) has become a recognised and effective method of treating erythema and telangiectasia. The latest recommendations emphasise the advantage of combining subjective clinical assessments with objective imaging analyses in monitoring therapy effects. Methods: A total of 20 patients with rosacea qualified for this study. They were subjected to three polychromatic light procedures (Lumecca, Inmode; wavelength of 515–1200 nm) at 21-day intervals. The skin condition was documented photographically, and the degree of erythema was assessed on the basis of the Clinician Erythema Assessment (CEA) scale and objective analysis of the skin texture, using the parameters of contrast and homogeneity of the grey level co-occurrence matrix (GLCM). Results: A series of three polychromatic light treatments yielded a significant clinical improvement in all patients. The mean CEA value decreased by 61.11%, whereas the GLCM contrast in all the analysed facial areas dropped by about 17%, and homogeneity increased by 4–5%. The effects persisted for at least three months after the treatments. A high correlation of CEA scale results with GLCM parameters (R = 0.81–0.94 for contrast; R = −0.77 to −0.83 for homogeneity) was observed. Conclusions: Three polychromatic light treatments proved to be a very effective method of reducing erythema in rosacea, confirmed by both clinical evaluation and objective imaging analysis. The effects of therapy were durable and clear. Integration of the subjective method (CEA) with GLCM analysis can be a path for future research and clinical practice in the assessment of erythematous skin lesions. Full article

Electroencephalography (EEG)-based motor imagery (MI) brain–computer interfaces (BCIs) hold considerable potential for applications in neuro-rehabilitation and assistive technologies. Yet, their development remains constrained by challenges such as low spatial resolution, vulnerability to noise and artifacts, and pronounced inter-subject variability. Conventional approaches, including common spatial patterns (CSP) and convolutional neural networks (CNNs), often exhibit limited robustness, weak generalization, and reduced interpretability. To overcome these limitations, we introduce EEG-GCIRNet, a Gaussian connectivity-driven EEG imaging representation network coupled with a regularized LeNet architecture for MI classification. Our method integrates raw EEG signals with topographic maps derived from functional connectivity into a unified variational autoencoder framework. The network is trained with a multi-objective loss that jointly optimizes reconstruction fidelity, classification accuracy, and latent space regularization. The model’s interpretability is enhanced through its variational autoencoder design, allowing for qualitative validation of its learned representations. Experimental evaluations demonstrate that EEG-GCIRNet outperforms state-of-the-art methods, achieving the highest average accuracy (81.82%) and lowest variability (±10.15) in binary classification. Most notably, it effectively mitigates BCI illiteracy by completely eliminating the “Bad” performance group (<60% accuracy), yielding substantial gains of ∼22% for these challenging users. Furthermore, the framework demonstrates good scalability in complex 5-class scenarios, performing competitive classification accuracy (75.20% ± 4.63) with notable statistical superiority (p = 0.002) against advanced baselines. Extensive interpretability analyses, including analysis of the reconstructed connectivity maps, latent space visualizations, Grad-CAM++ and functional connectivity patterns, confirm that the model captures genuine neurophysiological mechanisms, correctly identifying integrated fronto-centro-parietal networks in high performers and compensatory midline circuits in mid-performers. These findings suggest that EEG-GCIRNet provides a robust and interpretable end-to-end framework for EEG-based BCIs, advancing the development of reliable neurotechnology for rehabilitation and assistive applications. Full article

Building Information Modeling (BIM) is increasingly used to support green building design practices, yet its alignment with established green building assessment (GBA) tools remains underexamined. This study evaluates the extent to which Autodesk Revit, as a BIM tool, supports the calculation of energy-related indicators in GBA tools such as the Leadership in Energy and Environmental Design (LEED) method. A quasi-empirical, multi-method approach was employed, combining content analysis, a Revit-based simulation of a residential building, and structured evaluation by a panel of four experts. Using both subjective and objective measures, the experts assessed Revit’s effectiveness and the role of Revit’s media channels—modeling, simulation, data integration, and text documentation—in supporting and calculating LEED Energy and Atmosphere (EA) indicators. Results reveal that Revit is capable of effectively supporting 7 out of 11 LEED EA indicators. The highly supported indicators included minimum energy performance, building-level energy metering, optimized energy performance, advanced energy metering, renewable energy production, and enhanced refrigerant management while the fundamental refrigerant management indicator was evaluated as a moderately supported indicator. These highly supported indicators are core energy-related indicators; three of them are prerequisite indicators, while the remaining are credit indicators that cover 66.7% of the weight assigned for the EA indicators. The results also demonstrated that the remaining four indicators—fundamental commissioning and verification, enhanced commissioning, demand response, green power, and carbon offsets—were evaluated as poorly supported by Revit. The consistency of results across two rounds of survey, along with the expert’s consensus on 73% (8 out of 11) of the examined indicators, provides empirical validation of Rivet’s capacity to support LEED GBA. Findings also showed that modeling and simulation, followed by data integration, are the most impactful channels in supporting and calculating LEED EA criteria and requirements, with significant statistical correlation confirmed through Kendall’s Tau correlation. The findings have theoretical and practical implications for designers, green building practitioners, and BIM developers and suggest areas for further research. Full article

Equipment failure is the leading cause of industrial operational disruption, with unplanned downtime accounting for up to 11% of manufacturing revenue, highlighting the need for effective proactive maintenance strategies, such as protective sensors that can detect potential failures in critical equipment before a functional failure occurs. However, sensors are also subject to hidden failures themselves, requiring periodic failure-finding inspections. This study proposes a novel integrated multimethodological approach combining discrete event simulation, Monte Carlo, optimization, risk analysis, and multicriteria decision analysis methods to determine the optimal inspection period for protective sensors subject to hidden failures. Unlike traditional single-objective models, this approach evaluates alternative inspection periods based on their risk-informed overall values, considering multiple conflicting key performance indicators, such as maintenance costs and equipment availability. The optimal inspection period is then selected considering uncertainties and the intertemporal, intra-criterion, and inter-criteria preferences of the organization. The approach is demonstrated through a case study at the leading Portuguese electric utility, replacing previous empirical inspection standards that did not consider economic costs and uncertainties, supported by an open, transparent, auditable, and user-friendly decision support system implemented in Microsoft Excel using only built-in functions and modeled based on the principles of probability management. The results identified an optimal inspection period of 90 h, representing a risk-informed compromise distinct from the 120 h interval suggested by cost minimization alone, highlighting the importance of integrating organizational preferences into the decision process. A sensitivity analysis confirmed the robustness of this solution, maintaining validity even as the organizational weight for equipment availability ranged between 35% and 82%. The case study shows that the proposed approach enables the identification of inspection intervals that lead to quantitatively better maintenance cost and availability outcomes compared to empirical inspection standards. Full article

The ethical and legal governance of Animal-Assisted Interventions (AAIs) remains conceptually and normatively fragmented. Although animals engaged in therapeutic, educational, and assistive activities make valuable contributions to human well-being, they continue to be defined by law as property or welfare objects, despite their meaningful yet limited forms of relational participation within structured human-controlled environments. This perspective obscures their context-dependent responsiveness and their institutional embeddedness. The present paper addresses this gap by adopting a normative and interdisciplinary approach grounded in relational legal theory and vulnerability scholarship. The concept is developed by drawing on Jennifer Nedelsky’s notion of relational autonomy and Martha Fineman’s theory of universal vulnerability. This results in the conceptualisation of AAI animals as correlated subjects: beings whose ethical and legal significance derives from the relationships and institutional contexts that shape their participation. The analysis identifies weaknesses in current medico-legal practices that frame veterinary certification and welfare assessment as static technical acts, ignoring their relational and systemic dimensions. The paper puts forward a relational ethical–legal framework for Animal-Assisted Interventions, centred on relational vulnerability, context-sensitive oversight and continuous institutional accountability. A number of practical recommendations are put forward, including the introduction of renewable ethical licences, inter-institutional monitoring and the establishment of multidisciplinary oversight mechanisms. By redefining animals’ normative status through relational ethics, in alignment with the interconnected human, animal, and environmental dimensions emphasized by the One Welfare principles, the study advances a shift from welfare-based protection toward a model of justice grounded in interspecies interdependence and institutional responsiveness. Full article

Fine and ultra-fine sugarcane bagasse (SCB) fractions (≤200 μm) that are naturally generated during industrial grinding have been systematically overlooked in lignocellulosic pretreatment research. Previous studies have largely relied on commercially processed pulps or coarse particles (>200 μm), typically without systematic size fractionation. Here, we demonstrate that these fine fractions—including ultra-fines (≤45 μm), which are often excluded from analytical workflows due to concern about excessive degradation—are viable feedstocks for producing lignin-containing cellulose nanofibers (LCNF) via a sequential thermal hydrolysis treatment (THT)–deep eutectic solvent (DES) pretreatment specifically designed to retain lignin. Size-fractionated SCB (≤45, 45–100, and 100–200 μm) was subjected to THT (190 °C, 15 min), followed by DES treatment using choline chloride/urea (1:2 molar ratio, 130 °C, 2 h). Multi-technique characterization using Fourier transform infrared spectroscopy (FT-IR), thermogravimetric analysis (TGA), and X-ray diffraction (XRD) indicated substantial hemicellulose removal (>70%), effective lignin retention (7.6–9.1%), cellulose enrichment (74.0–77.5%), and preservation of cellulose I structure allomorph. The crystallinity index increased from 46.5–52.7% after THT to 56.7–57.2% after DES treatment, and notably, uniform compositional and structural features were obtained across all particle size classes after DES treatment. Subsequent high-pressure microfluidization (700 bar, five passes) yielded LCNF with consistent morphology across all fractions: uniform fibril diameters (24.6–26.2 nm), a discernible lignin coating, and excellent colloidal stability (zeta potential: −86.3 to −95.0 mV). Field emission scanning electron microscopy (FE-SEM) and transmission electron microscopy (TEM) confirmed well-dispersed nanofibrous networks. Collectively, these findings show that the full range of fine SCB fractions can be effectively valorized into high-performance LCNF through sequential THT–DES pretreatment, enabling comprehensive utilization of industrial grinding outputs and advancing circular bioeconomy objectives. Full article

With the rapid development of cross-sea infrastructure, the immersed tube method has been increasingly applied to deep-water immersed-tube tunnel construction. However, when the construction depth reaches the scale of one hundred meters, issues such as high hydrostatic pressure, complex hydrological conditions, and limited construction windows significantly elevate project risks. Against this backdrop, this study systematically reviews relevant domestic and international research findings in the context of 100-m-deep water environments and constructs a comprehensive risk index system covering the construction processes of the WBS breakdown system based on the WBS-RBS decomposition method within the HSE framework. A risk index weighting analysis combines quantitative and qualitative analysis, categorizing the indicators into qualitative and quantitative categories. Quantitative analysis employs threshold determination and the LEC method; qualitative analysis utilizes expert surveys and the G1 method. Ultimately, a model that combines multiple methods for a 100-m-deep water environment, integrating subjective expertise and objective data, is developed. On this basis, multi-level prevention and control measures are proposed for hundred-meter-deep water-immersed tube construction. The results demonstrate that the proposed system can effectively identify key risk sources under deep-water conditions and provide practical countermeasures, offering significant guidance for ensuring construction safety and engineering quality in hundred-meter immersed-tube tunnel projects. Full article

Objective: Giant cell lesions (GCLs) share similar histopathologic features. The influence of immune involvement on the biology of giant cell lesions remains largely elusive. This study aimed to evaluate and compare lymphocyte and mast cell infiltration and distribution among three giant cell lesions. Study design: A total of 30 FFPE tissue blocks, comprising 10 PGCGs, 10 CGCGs (aggressive and nonaggressive), and 10 GCTs (aggressive and nonaggressive) of bone, were subjected to IHC staining for CD3 and CD20 lymphocyte markers and toluidine blue staining for mast cells. The mean count of positively stained cells was calculated and categorized into three scores, along with a group for negative cases. Statistical analysis was conducted to assess significance at p < 0.05. Result: Lymphocyte infiltration was observed across all lesions. CD3⁺ and CD20⁺ cell counts were significantly elevated in PGCGs, followed by CGCGs, and were lowest in GCTs of bone. In contrast, mast cell counts were high in GCTs of bone and CGCGs and low in PGCGs. Aggressive giant cell lesions of bone showed a significantly low number of CD3⁺ and CD20⁺ cells (Mann–Whitney U test; p = 0.05, 0.004) and a high number of mast cells (Mann–Whitney U test; p < 0.001) compared with nonaggressive lesions of bone. PGCGs and nonaggressive CGCGs showed comparable CD3 expression, with no significant difference between them (p = 0.59). CD20 levels were higher in nonaggressive CGCGs but did not reach statistical significance (Mann–Whitney U test; p = 0.07). Mast cell density was significantly lower in PGCGs compared with intraosseous nonaggressive CGCGs. Conclusions: The present study shows that GCTs of bone, CGCGs, and PGCGs possess distinct immune microenvironmental profiles. Aggressive lesions demonstrate reduced lymphocyte infiltration and increased mast cell density, a pattern particularly evident in GCTs of bone. This imbalance may contribute to their aggressive behavior by enabling them to escape host immune regulation. Full article

Background/Objectives: Alzheimer’s disease (AD) requires accessible and non-invasive biomarkers that can support early detection, especially in settings lacking specialized expertise. Sonification techniques may offer an alternative way to convey neurophysiological information through auditory perception. This study aimed to evaluate whether human listeners without EEG training can discriminate between sonified electroencephalographic (EEG) patterns from patients with AD and healthy controls. Methods: EEG recordings from 65 subjects (36 with Alzheimer’s, 29 controls) from the Open-Neuro ds004504 dataset were used. Data were processed through sliding-window spectral analysis, extracting relative band powers across five frequency bands (delta: 1–4 Hz, theta: 4–8 Hz, alpha: 8–13 Hz, beta: 13–30 Hz, gamma: 30–45 Hz) and spectral entropy, aggregated across 10 topographic regions. Extracted features were sonified via parameter mapping to independent synthesis sources per frequency band, implemented in an interactive web interface (Tone.js v14.8.49) enabling auditory evaluation. Eight evaluators without EEG experience blindly classified subjects into two groups based solely on listening to the sonifications. Results: Listeners achieved a mean classification accuracy of 76.12% (SD = 17.95%; range: 49.25–97.01%), exceeding chance performance (p = 0.001, permutation test). Accuracy variability across evaluators suggests that certain auditory cues derived from the sonified features were consistently perceived. Conclusions: Parametric EEG sonification preserves discriminative neurophysiological information that can be perceived through auditory evaluation, enabling above-chance differentiation between Alzheimer’s patients and healthy controls without technical expertise. This proof-of-concept study supports sonification as a complementary, accessible method for examining brain patterns in neurodegenerative diseases and highlight its potential contribution to the development of accessible diagnostic tools. Full article

Background/Objectives: Ageism is a pervasive form of prejudice that undermines health, social participation, and intergenerational solidarity, yet validated research tools for measuring ageism are lacking in many countries. The Fraboni Scale of Ageism (FSA) is one of the widely used instruments, but its psychometric properties have not previously been examined in the Czech context. This study aimed to translate the 29-item FSA, evaluate its reliability and validity, and describe ageism across generations. Methods: A quantitative cross-sectional survey based on face-to-face interviews was conducted in March 2024 among the Czech population aged 15–74 years (n = 1096). Data analysis included descriptive statistics, internal consistency indices (Cronbach’s α, McDonald’s ω, Composite Reliability, Average Variance Extracted), exploratory factor analysis (EFA) on a random half-sample, and confirmatory factor analysis (CFA) on the second half. Construct validity was also examined. Results: The Czech FSA showed very good distributional characteristics with no floor or ceiling effects and excellent internal consistency (α = 0.949; subscales α = 0.848–0.898). EFA replicated the original three-factor structure (Antilocution, Avoidance, and Discrimination) explaining 57.6% of variance. CFA supported this structure with good-to-excellent model fit. FSA scores increased systematically from Baby Boomers to Generation Z, indicating higher ageism among younger cohorts. Higher fear of old age, lower education, an earlier subjective boundary of old age, and absence of an older co-resident were associated with higher ageism scores. Conclusions: The Czech version of the FSA is a reliable and valid instrument for assessing ageist attitudes in the Czech population. Its robust psychometric properties and sensitivity to theoretically relevant correlates support its use for monitoring ageism, evaluating interventions, and enabling cross-national comparisons in aging research and policy. Full article