Search Results (566)

Background: Reduced physical fitness in individuals with schizophrenia contributes to disability and health disparities, highlighting the need for valid and responsive field measures in exercise interventions. Objective: This study examined the long-term stability, construct validity, and responsiveness of the Six-Minute Walk Test (6MWT) in individuals with schizophrenia undergoing structured exercise interventions. Methods: This secondary analysis included 70 participants from two randomized controlled trials of 12-week Baduanjin or brisk walking interventions. The cohorts were pooled after confirming comparable baseline characteristics and no significant group-by-time interaction in 6MWT change. Baseline and post-intervention assessments included the 6MWT, the Timed Up-and-Go (TUG), the cognitive dual-task TUG (TUGcognitive), and the 30-Second Chair Stand Test (30CST). Long-term stability of 6MWT scores was assessed using the intraclass correlation coefficient (ICC), and measurement error was estimated using the standard error of measurement (SEM) and minimal detectable change at the 95% confidence level (MDC₉₅). Construct validity was examined using Spearman correlations (ρ), and responsiveness was examined using the standardized response mean (SRM) and Cohen’s d. Results: The 6MWT showed excellent long-term stability (ICC = 0.96, 95% CI: 0.93–0.97), with SEM = 13.41 m and MDC₉₅ = 37.19 m. Construct validity was supported by correlations with the TUG (ρ = −0.54, p < 0.001), 30CST (ρ = 0.45, p < 0.001), and TUGcognitive (ρ = −0.36, p = 0.002). Responsiveness was large (SRM = 1.08, 95% CI: 0.84–1.31), with a complementary effect size of d = 0.32 (95% CI = 0.24 to 0.42), and 24.29% of participants exceeded the MDC₉₅ threshold. Conclusions: The 6MWT demonstrated appropriate long-term stability, construct validity, and responsiveness as a measure of functional exercise capacity in schizophrenia, supporting its use for evaluating exercise outcomes in psychiatric rehabilitation. Because the present psychometric analysis did not include a non-exercise comparison group, the responsiveness estimates reflect within-intervention change and should not be interpreted as causal treatment effects of exercise. Larger studies are needed to identify responder characteristics and trajectories of changes in test performance. Full article

Sentiment analysis of multimodal social media data is of great importance, not only for recognizing objective information but also for capturing subjective emotional states. While single-modal sentiment analysis has achieved notable progress, existing multimodal approaches still face two key challenges: (1) inadequate modeling of subjective emotional characteristics and (2) insufficient handling of cross-modal inconsistencies. To address these limitations, we propose an image-text multimodal sentiment analysis framework (CogSent) grounded in the psychological Dual-System Theory. First, inspired by human fast and slow thinking, we develop a Hierarchical Dual-Channel Cognition (HDCC) architecture to extract intuitive and rational affective features, respectively. Second, we introduce an Intuition-Guided Cognition Refinement (IGCR) module that uses System-I-inspired intuitive representations as affective priors to retrieve and refine System-II-inspired contextual representations via cross-attention. Third, we propose a Dynamic Cross-Modal Cognition Fusion (${\mathrm{DC}}^2$F) network that predicts sample-adaptive thresholds from modality discrepancy, agreement, and attention statistics, dynamically regulating directional image–text interaction to mitigate interference from conflicting cross-modal sentiment signals. Extensive experiments on public benchmarks demonstrate that CogSent achieves improved performance compared to existing methods and yields competitive results on multiple evaluation settings. Full article

Commercialisation of research outcomes depends not only on technological quality but also on the competences through which research organisations identify market opportunities, coordinate stakeholders and translate knowledge into sustainable value. This study identifies and classifies commercialisation competences in research network organisations and develops a time-structured framework for operationalising their contribution to sustainability-oriented innovation (SOI). A structured review of Scopus and Web of Science publications, using predefined relevance criteria, yielded 129 competence formulations. Competence extraction was conducted by one author, while two authors independently synthesised the formulations into 25 conceptually distinct competences: five cognitive, eight functional, four personal and eight meta-competences. The 25 competences were then mapped against the triple bottom line, dynamic capabilities and ESG perspectives through a consensus-based expert assessment. Ten competences were classified as core sustainability-oriented, twelve as enabling and three as neutral. Because this classification is interpretative rather than empirically validated, it is intended as a transparent analytical proposition for subsequent testing. Each competence was linked to an Activity–Process Performance–Outcome (A–S–W) structure based on leading, diagnostic and lagging indicators, producing 75 illustrative indicators. The proposed numerical thresholds are heuristic calibration examples rather than universal benchmarks. The framework connects competence activation with process quality and commercialisation outcomes while incorporating economic, environmental and social dimensions and provides a basis for competence development, performance monitoring and future empirical validation. Full article

Background/Objectives: Eating disorders are increasingly conceptualized as information-processing disorders characterized by attentional biases toward food-related stimuli. However, whether such biases are already detectable in subclinical, non-treatment-seeking populations remains unclear. This study examined whether subclinical eating pathology, assessed with the Eating Attitudes Test-26 (EAT-26), is associated with distinct patterns of visual attention toward high- and low-calorie food images in university students. Methods: In this cross-sectional observational study featuring an experimental eye-tracking task, 89 university students completed the EAT-26 and a visual task displaying paired high- and low-calorie food images alongside neutral controls. Oculomotor metrics included first fixation duration (FFD), fixation count (FC), and average fixation duration (AFD). Data were evaluated using EAT-26 threshold-based group stratification (lower-risk vs. risky eating behavior) and Spearman rank correlation analyses. Results: Global EAT-26 scores showed a significant correlation with a directional attentional bias index (rho = 0.29, p = 0.006). The Dieting subscale demonstrated no significant relationships with any oculomotor metrics. Conversely, Oral Control scores were significantly negatively correlated with the directional attentional bias index (rho = −0.27, p = 0.009) and positively tracked with low-calorie fixation counts (rho = 0.30, p = 0.004). Bulimia subscale scores showed a moderate positive correlation with the directional attentional bias index (rho = 0.26, p = 0.013), characterized by a significant decrease in low-calorie fixation counts (rho = −0.32, p = 0.002) and a strong increase in high-calorie fixation counts (rho = 0.36, p < 0.001) during sustained viewing. Conclusions: Subclinical eating pathology tendencies are associated with distinct implicit attentional profiles regarding food caloric density during sustained cognitive evaluation. Oral control drives visual prioritization of low-calorie stimuli to maintain inhibitory control, whereas bulimic tendencies reflect prolonged visual preoccupation with high-calorie reward cues. Eye-tracking represents a promising non-invasive research tool for exploring early cognitive correlates of eating-disorder risk. Full article

This study aims to systematically assess urban Chinese college students’ awareness and depth of understanding of the Sustainable Development Goals (SDGs), examine how digital media exposure and academic discipline shape SDG-related cognitive development, and provide empirical evidence to inform the design of sustainable development education in higher education institutions. A questionnaire survey was administered in China. Descriptive statistics, multinomial logistic regression, path analysis, and correlation analysis were employed to examine the relationships among digital media use, urban context, disciplinary background, and SDG cognition. The results are as follows. Digital media exposure and city tier were both associated with variations in SDG cognition, and a significant nonlinear threshold was observed at approximately two hours of daily media use. A clear threshold effect emerges, with students using digital media for more than two hours per day demonstrating markedly higher cognitive levels. Although overall awareness is relatively high, knowledge remains broad but superficial, with weaker understanding of ecological and collaborative goals. Disciplinary differences are evident—medical and agricultural students show stronger comprehension, while arts and humanities students lag behind—yet support for interdisciplinary collaboration is substantial. Participation in SDG-related learning activities significantly enhances attitudinal and behavioral change. This study advances the literature by integrating digital media exposure, urban hierarchy, and academic discipline into a unified analytical framework to explain variations in SDG cognition among Chinese urban college students. It identifies a significant media use threshold effect (over two hours per day) that enhances cognitive accumulation, revealing a nonlinear mechanism rarely examined in prior research. By uncovering disciplinary heterogeneity and the relative weakness in ecological and collaborative goal awareness, the study moves beyond descriptive assessments to provide targeted, evidence-based implications for curriculum design and interdisciplinary sustainable development education in higher education institutions. Full article

Introduction: Mild cognitive impairment (MCI) is a transitional stage between normal ageing and dementia, affecting ~35% of adults aged 70+ and carrying a 15–18% annual risk of progression. Cognitive training (CT) shows promise but outcomes are variable and transfer to daily function is unclear; intermittent theta burst stimulation (iTBS) may enhance prefrontal neuroplasticity. Few studies have evaluated whether combining CT and iTBS in MCI is practical, acceptable, and safe. Methods: This 18-week, randomised, double-blind, sham-controlled feasibility pilot trial will recruit 44 individuals with MCI, randomised 1:1 to CT + active iTBS or CT + sham iTBS. Participants complete 14 CT sessions over 10 weeks; accelerated iTBS is delivered in five sessions per day over five consecutive days at 75% resting motor threshold to the left DLPFC using neuronavigation, with reversed-coil sham. Primary outcomes are feasibility, acceptability, adherence, and safety; secondary (exploratory) outcomes are cognitive, functional, and psychological; tertiary (mechanistic) outcomes are EEG- and TMS-derived neurophysiological measures. The trial is not powered for efficacy: feasibility and neurophysiological outcomes will be analysed descriptively, while secondary outcomes will be analysed using linear mixed-effects models. Ethics and dissemination: Ethical approval has been granted by the Western Sydney University HREC (H16500); written informed consent will be obtained before enrolment. Trial registration number: ACTRN12625000952448. Full article

Background: Over the last decade, numerous studies have investigated the administration of monoclonal anti-amyloid antibodies (AAAs) as a therapeutic approach in Alzheimer’s disease (AD). The purpose of this umbrella review is to summarize current knowledge concerning the efficacy and safety of FDA- and EMA-approved AAAs for AD, namely, lecanemab and donanemab. Methods: We conducted a literature search in the PubMed, Scopus, and Web of Science databases in English, focusing on systematic reviews and/or meta-analyses, assessed by AMSTAR 2, concerning clinical and imaging efficacy, i.e., cognitive improvement and reduction of beta-amyloid on PET scan, as well as safety, i.e., adverse events and amyloid-related imaging abnormalities (ARIA). The extracted review-level dataset was entered into SPSS Version 26 for descriptive statistical analysis. Results: This umbrella review included 11 systematic reviews and/or meta-analyses. Patients treated with lecanemab or donanemab showed statistically significant changes on cognitive scales such as the Clinical Dementia Rating-Sum of Boxes (CDR-SB) (mean effect estimate −0.485, SD = 0.152, −0.70 to −0.34) and the Alzheimer’s Disease Assessment Scale-Cognitive Subscale (ADAS-Cog), but most were below or around clinically meaningful thresholds. Lecanemab and donanemab showed a statistically significant decrease in amyloid PET outcomes, including centiloids or the standardized uptake value ratio. Both antibodies were linked to ARIA, including amyloid-related imaging abnormalities-edema (ARIA-E OR 8.32–12.26) and amyloid-related imaging abnormalities-hemorrhage (ARIA-H OR 2–5.77), especially in ApoEε4 carriers. Conclusions: Lecanemab and donanemab are biologically active drugs for the treatment of early AD, with cognitive benefits below or around the clinically meaningful threshold. They are, however, associated with increased ARIA risk. Their administration depends upon careful patient selection, shared decision-making, and clear communication regarding expectations. Full article

Background: Orthodontic treatment is a long-term intervention in which patient satisfaction is an important outcome alongside clinical measures. This study aimed to translate and culturally adapt the Orthodontic Patient Satisfaction Questionnaire (OPSQ) into Malay (M-OPSQ), evaluate its content validity, face validity, internal consistency and structural validity, and assess satisfaction following fixed appliance treatment. Methods: Content validity was evaluated by eight orthodontists using the Content Validity Index and Content Validity Ratio. Translation involved forward translation, cognitive debriefing, back translation and review by the original questionnaire developer. Face validity was assessed among 34 participants. Preliminary psychometric evaluation involved 159 adults recruited using convenience and snowball sampling. Internal consistency was assessed using Cronbach’s alpha, while structural validity was evaluated using exploratory and confirmatory factor analyses. Exploratory group comparisons were analysed using non-parametric tests. Results: Content and face validity assessments resulted in a final 31-item M-OPSQ. Participants had a mean age of 27.11 ± 8.02 years, and 72.3% were female. The mean total score was 159.18 ± 20.33, with excellent internal consistency (α = 0.954; 95% confidence interval (CI) 0.942–0.963). Exploratory factor analysis supported a three-factor structure. The three-factor confirmatory model showed better relative fit than the unidimensional model, although most fit indices remained outside acceptable thresholds. Exploratory analyses identified differences across treatment provider and setting groups. Conclusions: The M-OPSQ demonstrated acceptable content and face validity and excellent internal consistency among Malaysian adults who had completed fixed appliance orthodontic treatment. Independent confirmation of the proposed factor structure, together with further assessment of construct validity and test–retest reliability, is required. Full article

Background: Food noise describes persistent, intrusive thoughts about food, eating, and cravings that occur in the absence of physiological hunger. Its occurrence among healthcare students and professionals in Saudi Arabia is unknown. This study measured food noise in this group in Al-Ahsa, described the proportion meeting study-defined severity thresholds, and identified its main correlates. Methods: In this cross-sectional study, healthcare students and professionals in Al-Ahsa completed a bilingual (Arabic–English) electronic questionnaire capturing demographic and lifestyle characteristics, a 14-item food noise scale adapted from the Food Thought Suppression Inventory (each item rated 1–5; total range 14–70), the SCOFF eating disorder screen, and the four-item Perceived Stress Scale. The factor structure of the food noise scale was examined by exploratory factor analysis with parallel analysis and random split-half replication. Severity was graded from the mean item score as low, moderate, or high using exploratory thresholds, and associations were tested using t-tests, one-way analysis of variance, the Pearson correlation, and complete-case multivariable linear regression with robust standard errors and six sensitivity analyses. Results: Among 593 participants (mean age 25.7 years; 67.5% women; 60.0% students), the food noise scale was unidimensional (Kaiser–Meyer–Olkin 0.95; one eigenvalue above both unity and the parallel analysis threshold; 41.8% of variance explained; loadings 0.50 to 0.74) and internally consistent (Cronbach alpha 0.91). The mean total score was 41.9 (standard deviation 12.7). At least moderate food noise was present in 75.9% of participants (95% CI 72.3 to 79.2) and high food noise in 29.0% (95% CI 25.5 to 32.8). A positive SCOFF screen was recorded in 70.2% (95% CI 66.3 to 73.7), and the mean perceived stress score was 8.1 (standard deviation 2.8). In the adjusted model (n = 573; unadjusted R-squared 0.279, adjusted R-squared 0.266), food noise was independently associated with the SCOFF score (B 3.85 per point) and perceived stress (B 0.69 per point), both of which held across every sensitivity analysis, although both relationships proved concave rather than linear. Weaker associations with age (B 0.19 per year) and any night shift work (B 2.45) did not survive alternative model specifications, and crude differences by sex, role, weekly hours, and fasting did not persist after adjustment. Conclusions: Food noise was common in this sample and tracked eating disorder risk and perceived stress more closely than demographic or occupational characteristics. Because recruitment was by convenience and the severity thresholds are exploratory rather than validated, the proportions reported here describe this sample and should not be read as population prevalence. The findings provide a first benchmark for the construct in this population and support attention to the cognitive dimension of eating within health professions settings. Full article

Background/Objectives: Unilateral Spatial Neglect (USN) is a disabling attentional syndrome occurring after cortical or subcortical stroke, including thalamic lesions. EEG-based neurofeedback (EEG-NF) may support cortical self-regulation, but evidence in spatial neglect remains limited. This case report describes the clinical, neuropsychological, functional, and electrophysiological (quantitative EEG, qEEG) evolution of a patient with USN after a right thalamic hemorrhagic stroke who underwent multidisciplinary rehabilitation including EEG-NF. Methods: A 70-year-old patient underwent a 3-week inpatient multidisciplinary rehabilitation program including physiotherapy, speech and swallowing therapy, conventional cognitive stimulation, and 15 adjunctive EEG-NF sessions. Baseline and post-treatment assessments included clinical, neuropsychological, neglect-specific, functional, affective, and resting-state qEEG measures. Individual change was examined using the Reliable Change Index when suitable psychometric parameters were available, together with published normative and clinical thresholds. Results: After rehabilitation, the Montreal Cognitive Assessment total raw score increased from 20 to 24, reaching the published minimal clinically important difference but not the minimal detectable change. The Frontal Assessment Battery increased from 8 to 12; after adjustment for age and education according to Italian normative data, both scores remained below the normative cut-off. Neglect-specific measures showed reduced spatial asymmetry, increased contralesional target detection, and a Catherine Bergego Scale reduction from 17 to 5, indicating a shift from moderate to mild ecological neglect. Functional independence improved, with reliable change in Functional Independence Measure (FIM) total and cognitive scores and Modified Barthel Index scores. Exploratory qEEG analyses showed condition-dependent spectral and connectivity changes, but findings were heterogeneous and hypothesis-generating. EEG-NF was completed without adverse events. Conclusions: The adjunctive EEG-NF protocol was completed as planned, with no adverse events. Clinical improvement cannot be attributed specifically to neurofeedback because all rehabilitation components were delivered concurrently. Controlled studies are needed to clarify its specific contribution and the durability of the observed improvements in post-stroke spatial neglect. Full article

The Olfactory System is receiving increasing attention in recent years as a potential biomarker for Alzheimer’s disease (AD). Early-stage AD is often associated with a decline in olfactory function, with studies suggesting that olfactory memory deficit may precede cognitive symptoms. We explore the intricate relationship between the Olfactory System and Alzheimer’s disease, examining both the neuroanatomical and physiological changes that occur in the olfactory pathways during the progression of AD. Memory, as a functional feature, was modeled using artificial neural networks, and it was related to the macro-parameters of the network. While these networks cannot completely capture the intricacies and functions of the human brain, they provide a clear understanding of how processes occur within it. Neural networks exhibited memory domains, defined by stable and unstable steady states; the former can be considered a prerequisite for memory storage and recall; the latter can be considered threshold values between stable steady states. Additionally, by introducing division of the neural population into subpopulations, the networks manifested multiple stable states, corresponding to multiple memory domains, which in a qualitative manner suggest hierarchically organized nonlinear complexity and multi-scale self-similarity of memory processes. Full article

The discovery of the glymphatic system and meningeal lymphatic vessels established that the brain possesses an organized lymphatic clearance network that drains to the deep cervical lymphatics. Disruption of this system has been suggested to contribute to the accumulation of pathogenic proteins implicated in neurodegeneration. Cervical lymphatic reconstruction has been associated with some neurological benefit in Alzheimer’s and Parkinson’s disease, and preclinical work has demonstrated that noninvasive manipulation of superficial cervical lymphatics can increase cerebrospinal fluid outflow. Whether noninvasive cervicofacial lymphedema therapy can produce comparable neurological effects remains unknown. We report two men with Parkinson’s disease (Hoehn and Yahr stages 2.5 and 3) treated with a standardized cervicofacial lymphedema therapy protocol targeting cervical and facial lymphatic pathways. Total MDS-UPDRS scores decreased by 19 points (34.5%) in Patient 1 and 5 points in Patient 2. The reduction in Patient 1 exceeded the published threshold for clinically meaningful total-score improvement. Benefits were reproducible and session-linked, and were accompanied by motor and non-motor gains in cognition, alertness, mood, energy, and sleep; interruption of therapy was associated with return toward baseline. Cervicofacial lymphedema therapy may represent a low-risk, noninvasive intervention hypothesized to influence brain lymphatic clearance in Parkinson’s disease. Full article

(1) Background/Objectives: Blood-based biomarkers have emerged as practical tools for identifying Alzheimer’s disease (AD) pathology in patients with mild cognitive impairment (MCI). Among them, plasma phosphorylated Tau217 (p-Tau217) demonstrates strong associations with cerebral amyloid deposition. In parallel, the easy Z-score Imaging System (eZIS), a quantitative brain perfusion SPECT analysis tool, has been widely used to detect characteristic AD-related hypoperfusion patterns. Although both measures reflect distinct AD processes, the relationship between plasma p-Tau217 and eZIS in MCI remains unclear. (2) Methods: This retrospective study included 62 patients with MCI who underwent plasma p-Tau217 testing and brain perfusion SPECT with eZIS analysis. Associations between plasma p-Tau217 and the three eZIS indices (severity, extent, and ratio) were evaluated. Exploratory subgroup analyses were performed using a previously reported plasma p-Tau217 threshold of 0.63 pg/mL. In addition, a validation sub-cohort of 21 participants who underwent plasma p-Tau217 testing, eZIS, and amyloid PET was analyzed to assess concordance with cerebral amyloid pathology. (3) Results: Among the three eZIS indices, severity demonstrated the highest sensitivity relative to elevated plasma p-Tau217 levels. However, all eZIS indices showed limited discriminative performance. Optimal eZIS cutoff values derived from the present cohort were higher than previously reported thresholds. In the amyloid PET-validated sub-cohort, plasma p-Tau217 demonstrated closer concordance with amyloid positivity than any individual eZIS parameter. The reduced performance of eZIS appeared to be associated with advanced age, substantial vascular burden, white matter lesions, and cerebral atrophy. (4) Conclusions: Plasma p-Tau217 showed a stronger association with cerebral amyloid pathology than eZIS indices in this elderly MCI cohort. Nevertheless, eZIS may provide complementary information regarding downstream neurodegenerative and cerebrovascular processes that are not directly captured by plasma biomarkers. This integrated approach highlights plasma p-Tau217 as a primary screening tool for amyloid pathology to guide disease-modifying therapies (DMTs), alongside eZIS for tracking follow-up mixed co-pathologies. Full article

Akerlof’s classical theory of the “Market for Lemons,” which conceptualizes adverse selection driven by information asymmetry, established the foundation of information economics. While the traditional model assumes static equilibria among a limited number of agents, analyzing its behavioral dynamics within large-scale, complex network environments remains a highly relevant task in computational social science. This study extends the classical lemon market model into a nonlinear dynamical system on adaptive networks. We mathematically elucidate macro-level social phase transitions—specifically structural exclusion such as scapegoating and collective ostracism—induced by computational cognitive limits, and evaluate optimal intervention strategies to mitigate these systemic failures. Multi-agent simulations utilizing large-scale tensor operations demonstrate that autonomous edge rewiring under incomplete information does not merely result in the uniform displacement of high-quality goods as predicted by static theory. Instead, the network self-organizes into an irreversible structural division: a core group of influential agents monopolizes high-quality information, while marginalized agents are isolated into a peripheral “lemon echo chamber” where only low-quality information circulates. To address this structural pathology under a resource constraint limiting intervention to 10% of the total agents, we evaluated two distinct approaches. The results indicate that providing informational support to influential hubs functions as a trap that exacerbates systemic inequality, superficially elevating the overall market evaluation but permanently fixing the exclusion gap. Conversely, the forced maintenance and protection of “weak ties” bridging disconnected clusters constitutes the mathematically optimal solution to dissolve fragmentation, effectively eliminating the price gap and facilitating social inclusion. Furthermore, this study demonstrates that the mechanism of social exclusion exhibits strong hysteresis effects. A distinct tipping point governs the progression toward a fragmented lemon echo chamber. Interventions implemented after crossing this critical threshold fail to restore the system to its baseline state despite identical resource expenditure, confirming the presence of an irreversible phase transition. These findings establish that the collapse dynamics outlined in the classical lemon market serve as a generalized model for explaining contemporary collective ostracism driven by information cascades. Consequently, the analysis highlights the necessity of early intervention prior to critical thresholds and the systemic preservation of structural bypasses rather than post-hoc remediation. Full article

Aesthetic perception of rural streetscapes reflects individuals’ cognitive responses to their surroundings and is central to understanding how landscape preferences are formed. Existing studies using Scenic Beauty Estimation (SBE) are constrained by incomplete indicator systems and overreliance on linear approaches. This study proposes an interpretable machine learning framework that integrates multi-source data to examine the nonlinear influences of streetscape features on SBE. Using Sanguan Village, a water-networked settlement in Jiangsu, we developed a 24-indicator system spanning color, spatial, natural, artificial, and cultural dimensions. Based on 523 panoramic images and aesthetic ratings from 1175 respondents, we compared OLS, DT, MLP, SVR, RF, and XGBoost models. The best-performing XGBoost, combined with SHAP analysis, revealed threshold effects and interaction patterns among variables. Green visibility, architectural aesthetics, building visibility, sky visibility, environmental coordination, and water are the top six feature variables most strongly associated with rural streetscape aesthetic perception, and each exhibits threshold effects. The saturation threshold for green visibility is 0.153, and architectural aesthetics can only make a positive contribution when its score exceeds 3.815. The appropriate range for building visibility is below 0.452, while the optimal value for sky visibility is approximately 0.194. We also explored the context-dependence of these threshold effects across urban and rural settings. This study proposes streetscape optimization strategies focusing on screening key factors, controlling their thresholds, and coordinating the allocation of streetscape features. The interpretable analytical framework for rural scenic beauty established in this research can facilitate evidence-based landscape optimization and provide scientific support for sustainable rural development and tourism in this case. Full article