Search Results (144)

Scorpion venom peptides, with their stable disulfide backbone, compact structural framework, and highly selective regulation of ion channels, have long been regarded as important molecular probes in neuropharmacology. However, recent studies have revealed their potential for regulating oxidative stress, inflammation, and neuroprotection, making them a new research frontier. In this article, we focus on scorpion venom peptides as drugs, constructing an integrated knowledge framework from structural classification to clinical translation. First, scorpion venom peptides are systematically classified based on cysteine arrangement patterns and three-dimensional folding topology, and their structure–activity relationships are summarized. Based on this, the molecular mechanisms by which scorpion venom peptides regulate ion channels are systematically analyzed. We review the emerging pharmacological activities of scorpion venom peptides. Of particular note, the representative molecule SVHRSP has shown multi-target synergistic antioxidant and neuroprotective activity in models of Parkinson’s disease. We also systematically evaluate the application of engineering strategies, including cyclisation modification, nanodelivery, recombinant expression, and AI-assisted optimization, to overcome the translational bottlenecks in the development of scorpion venom peptides. However, it should be noted that most SVHRSP-related findings have been reported by a single research group; independent replication, pharmacokinetic characterization, and human efficacy data are still lacking. Its IND approval permits clinical investigation but does not yet constitute proven therapeutic benefit in patients. By integrating molecular structure, redox regulation mechanisms, and translational medicine perspectives, this review aims at providing a theoretical basis and practical pathways for scorpion venom peptides as precision therapeutic molecules for oxidative stress-related diseases. Full article

Promoting the high-quality development of farmers’ specialized cooperatives and narrowing regional development gaps is critical for advancing China’s rural revitalization strategy. Based on provincial panel data covering 30 Chinese regions from 2015 to 2023, this paper constructs a five-dimensional evaluation index system including standardized operation, operational performance, service scope, driving effect, and industrial upgrading, and adopts the entropy weight method to quantify the comprehensive development level of cooperatives. By combining spatial autocorrelation, kernel density estimation, the Dagum Gini coefficient and the Geodetector model, this paper explores the spatio-temporal evolution, regional disparities and multi-factor coupled driving mechanism of cooperative development. The main findings are as follows: (1) While the total quantity of cooperatives keeps expanding nationwide, their overall development level presents an evolutionary feature of declining first and then rising; industrial upgrading gradually becomes a new growth engine, whereas operational performance and driving effect slip downward. (2) The spatial layout of cooperatives maintains a typical pyramid structure; high-value agglomeration shifts from the Yangtze River Delta to southeast coastal regions, and low-value clusters are persistently concentrated in Northeast China. (3) The overall Dagum Gini coefficient reflects widening-then-shrinking regional gaps, and intra-eastern provincial differences constitute the primary source of nationwide spatial divergence. (4) Household consumption and rural labor force stock serve as core driving factors; regional economic development, agricultural production efficiency, rural human capital and land resource allocation form a coupled driving system, and all explanatory variables show mutual enhancement effects without offsetting interactions. Targeted policy suggestions are put forward to realize balanced and high-quality development of farmers’ specialized cooperatives across China. Full article

The rapid advancement of payment technologies and potential disintermediation pressure make it important to monitor how actively commercial banks participate in payment and settlement systems. This study conceptualizes bank participation as a multidimensional construct and develops a Bank Payment Participation Index (BPPI or ANR BPPI) using publicly available Reserve Bank of India data for 2011–2012 to 2022–2023. BPPI integrates Financial Capacity (FC), Technological Readiness (TR), Payment Performance (PI), and a PPI-based Technological Advancement/Disintermediation proxy (TAD). TAD, measured as the share of PPI transactions in total payment volumes, enters the index as (1−TAD) because rising non-bank payment penetration reduces banks’ intermediation share; a higher TAD represents a structural drag on bank payment participation, and (1−TAD) converts this drag into a participation-compatible scale. The index applies min–max normalisation, equal-weighted sub-index aggregation, and geometric mean composition with lagged input dimensions. Computations show that the four-component BPPI rises from 230.794 in 2013–2014 to 797.453 in 2022–2023, indicating a strong long-run increase in banking-system participation. The BPPI remains strongly associated with GDP over the 2013–2014 to 2022–2023 sample, with R Square = 0.906 and adjusted R Square = 0.894. Diagnostic tests indicate that the validation is best interpreted as association-based evidence rather than causal proof. The BPPI is proposed as a decomposable monitoring and diagnostic framework that equips regulators and banks to track participation trends and detect structural vulnerabilities over time, subject to future refinement using fixed policy goalposts, bank-level data, and CBDC-specific transaction data. In its present form, the BPPI constitutes a model-stage prototype framework subject to future operationalisation with fixed expert-determined benchmarks and bank-level disaggregated data. Full article

Selecting the appropriate academic track is a critical decision for students, as misalignment between program requirements and individual cognitive, personality, and competency profiles can significantly impact academic performance, persistence, and overall educational outcomes. Traditional educational recommender systems often rely solely on skill matching or on the correlation of interests, failing to account for the dimension of competency that is required for success in specific academic tracks. This paper introduces a novel Multi-Dimensional Psychometric Alignment (MDPA) algorithm that moves beyond simple rank-order correlation between skills and programs by jointly integrating multiple psychometric perspectives and evaluating both preference similarity and competency sufficiency. Based on a structured synthesis of Cognitive Preferences (MBTI), Cognitive Modalities (Gardner’s Multiple Intelligences), and Personality Stability (Big Five), the proposed profile captures complementary dimensions of student readiness that are usually examined separately in prior educational recommender systems. Then applies an alignment algorithm-which is based on a hybrid similarity metric that fuses Spearman’s Rank Correlation (Interest Shape) with Weighted Euclidean Distance (Competency Magnitude), enforced by non-linear threshold penalties for critical traits- in order to find the best options for students. This approach constitutes a deterministic, explainable recommender system whose novelty lies in combining heterogeneous psychometric evidence with an explicit magnitude–shape matching mechanism and threshold-based academic viability constraints. Our approach is validated through a case study of university students in Kazakhstan, and the results demonstrate how “academic fit” is better modeled as a function of both interest pattern and trait sufficiency, offering a robust alternative to “black-box” skill-based recommenders. Full article

To mitigate 3D spatial blockages and channel uncertainty in VHF/low-UHF UAV emergency networks, this paper presents a multimodal environment-aware framework for 3D virtual fluid antenna port scheduling within an Integrated Sensing, Computing, and Communication (ISCCC) architecture. Under rigorously verified spatial resolution and channel stationarity conditions, UAV micro-mobility is mapped onto a discrete 3D virtual port array, transforming continuous flight space into a controllable fluid antenna system (FAS). We define a spatial efficiency metric that quantifies the Pareto trade-off between spatial degrees of freedom and estimation error, parameterized by an error-sensitivity index, and prove the existence of a unique optimal flight scale. Utilizing a joint spatio-temporal channel model, we derive the irreducible entropy lower bound of channel uncertainty, demonstrating that intrinsic environmental randomness constitutes a fundamental predictability limit regardless of port density—a benchmark independent of any specific scheduling strategy. To ensure real-time viability, we introduce an ISCCC-inspired computation-and-caching strategy that leverages pre-calculated stationary probabilities to drive a multidimensional scoring mechanism incorporating channel entropy-based stability, predictive SNR, and load balancing. The suboptimality gap relative to a perfect-CSI oracle is analytically bounded, and proven to narrow significantly under the high temporal correlation inherent in VHF bands. Numerical results confirm that the proposed strategy attains 10.36 bps/Hz effective throughput and 10.5% outage probability, consistently outperforming rule-based, learning-based, and 2D spatial baselines, particularly under prolonged structural obstructions. Full article

To address the large deviation in annular trapped pressure prediction during testing and production stages of deepwater high-temperature and high-pressure wells, conventional models neglect the elastic uplift effect of the wellhead. This study overcomes the limitations of the plane strain model and establishes a three-dimensional thermos–hydro–mechanical coupled annular pressure prediction model based on the longitudinal stiffness constraint of the subsea wellhead. The deepwater wellbore–formation system is treated as a composite elastic structure. A generalized plane strain assumption is introduced to define the elastic boundary conditions and longitudinal segmentation characteristics of the wellhead. Based on generalized Hooke’s law, the three-dimensional stress–strain constitutive equation of casing is modified. A displacement model incorporating axial–radial coupling is derived, and an equivalent longitudinal stiffness coefficient of the wellhead is introduced. A coupled axial force equilibrium equation and a three-dimensional annular volume compatibility equation are established. Considering multi-annulus coupling, a volume compatibility matrix equation is formulated, and a successive approximation iterative algorithm with a relaxation factor is developed. Using a deepwater high-temperature, high-pressure gas well in the South China Sea as a case study, the effects of wellhead stiffness, free section length, and annular temperature rise on annular pressure are investigated via a single-variable method and compared with traditional rigid models. Results show that the subsea wellhead exhibits elastic uplift behavior. Its longitudinal stiffness has a reverse S-shaped nonlinear influence on annular pressure. Increasing the free section length significantly reduces annular pressure. The proposed model predicts values 17–21% lower than traditional rigid models, providing a more realistic representation of annular pressure evolution. The findings offer theoretical support and engineering guidance for deepwater well integrity design and annular pressure risk management. Full article

To elucidate the wear evolution and failure mechanisms of VL-type composite seals in aviation hydraulic actuators under multiple operating conditions, a two-dimensional plane-strain finite element model was developed for a VL seal consisting of a PTFE L-ring and an NBR O-ring. The model incorporated the Mooney–Rivlin hyperelastic constitutive law and the Archard wear model. The effects of O-ring compression ratio, hydraulic pressure, sliding velocity, and temperature on cumulative wear, wear rate, and contact state were systematically investigated. The results show that the compression ratio has a nonlinear influence on wear. Within 8–16%, the peak wear increases approximately linearly with compression ratio; above 16%, the peak wear reaches a plateau and a secondary wear zone appears, indicating a transition from single-contact to multi-contact sealing. Hydraulic pressure promotes wear over the range of 4–28 MPa, and at 28 MPa the opposite lip edge of the L-ring comes into contact with the cylinder wall, weakening the sealing effectiveness. Within 0.1–0.3 m/s, wear increases approximately linearly with sliding velocity. However, under high velocity and insufficient hydraulic pressure, the L-ring may undergo inversion, resulting in complete seal failure. Temperature exhibits a non-monotonic effect: material softening reduces local contact stress and wear from −55 to 80 °C, whereas excessive softening at 135 °C causes the peak wear rate to increase again. A parametric analysis scheme involving an increased L-ring height and thickness, a reduced O-ring cross-section diameter, and reserved deformation space raises the critical compression ratio for stable single-contact sealing from 16% to above 20%. These findings clarify the contact-stress/contact-area competition mechanism governing VL seal wear and provide guidance for the design of aviation hydraulic actuator seals. Full article

Academic satisfaction is positioned as a fundamental psychological construct with regard to academic success, linked to well-being and cognitive engagement. The aim of the study was to evaluate the satisfaction of secondary school students with high intellectual abilities (HIA) participating in the university mentoring program in the Basque Country Autonomous Community. A quantitative methodology was used with a sample of 90 students. A purpose-developed 17-item questionnaire with 17 items used to measure the different areas that make up the multidimensionality of satisfaction. The results indicate very high levels of overall satisfaction, with particular emphasis on the quality of the bond and the mentor’s expertise. Likewise, through confirmatory factor analysis (CFA), the validity of the instrument was tested under the ‘Big Four’ model (improvement-oriented learning, individualization, feedback and practical tasks with minimal transfer). It is concluded that the mentoring program used constitutes a suitable educational response that harmonizes intellectual challenge with the psychosocial support necessary to transform potential into talent. Full article

Deep coalbed methane (CBM) is a core exploration and development domain for increasing the reserves and production of unconventional natural gas in China. A systematic understanding has been established on the enrichment and accumulation mechanism of high-rank deep CBM in the southern section of the eastern margin of the Ordos Basin. However, the medium-rank deep CBM in the Mugua Area of the Shenfu Gas Field in the northern section of the eastern margin has essential differences from that in the southern section in terms of coal rank and hydrocarbon generation–occurrence mechanism, and its accumulation and enrichment regularity remain unclear. The core innovations of this study are as follows: aiming at the unclear accumulation regularity of medium-rank deep CBM in the northern section of the eastern margin of the Ordos Basin, we first reveal the spatiotemporal synergistic coupling reservoir-controlling mechanism of five factors (sedimentation–thermal evolution–temperature–pressure–preservation), determine the 1750 m critical transition zone of the deep CBM occurrence state, and establish two types of accumulation models adapted to the geological characteristics of medium-rank coal. Taking the No.8+9 coal seams of the Taiyuan Formation in the Mugua Area as the research object, based on the theoretical foundation of the dual properties of coal seams as the “source rock–reservoir”, this paper comprehensively adopted technical means such as core observation, drilling and logging data, and high-pressure isothermal adsorption experiments to carry out systematic multi-dimensional studies on sedimentary microfacies, coal reservoir characteristics, thermal evolution degree, and gas-bearing property; identified the main controlling factors of CBM accumulation; and constructed the accumulation model. The results show the following: ① The main burial depth of the coal seams is more than 1700 m, with a thickness ranging from 7.0 to 21.3 m and an average of 15.1 m, and the coal structure is dominated by the primary structure; maximum vitrinite reflectance (R_o,max) is generally distributed from 0.90% to 1.39% with an average of 1.08%, belonging to typical medium-rank coal; and the organic matter type is mainly Type III, with an average gas content of 10.01 m³/t, where the average proportion of desorbed gas in the total gas content is 83.91%, featuring superior source and reservoir conditions and a good foundation for CBM enrichment. ② The CBM accumulation in this area is jointly controlled by the coupling of four factors: sedimentation, thermal evolution degree, temperature–pressure effect, and preservation conditions. The tidal flat–lagoon facies control the development of high-quality coal seams; regional metamorphism dominates the hydrocarbon generation capacity and gas quality of coal seams; the temperature–pressure coupling forms a critical adsorption zone at 1750 m, defining the differentiation boundary of the occurrence state of deep CBM; and high-quality mudstone cap rocks, a stable structural environment, and closed hydrodynamic conditions constitute the three key guarantees for gas enrichment. ③ Two types of accumulation models are divided: “source–reservoir integration + multi-factor synergistic enrichment type” and “source–reservoir limited + insufficient accumulation condition type”. Among them, the four reservoir-controlling factors of the synergistic enrichment type are highly coupled, with excellent gas-bearing property and strong recoverability. This study systematically clarifies the enrichment and accumulation regularity of medium-rank deep CBM in the Mugua Area and improves the accumulation theory of medium-rank deep CBM in the northern section of the eastern margin of the Ordos Basin. Full article

Background/Objectives: Sarcopenia—the progressive loss of skeletal muscle mass and function—is a growing public health challenge in ageing populations. Island territories face compounded vulnerabilities due to distinct epidemiological and socio-economic profiles. This study examines sarcopenia risk prevalence among community-dwelling older adults in Tenerife (Canary Islands, Spain) and estimates the economic burden alongside the cost-effectiveness of evidence-based interventions. Methods: A cross-sectional study was conducted among 374 community-dwelling older adults (mean age 80.4 years, SD 4.8; 51.1% female) recruited from primary care health centres across three health zones in Tenerife. Participants were stratified into a control group without established chronic disease-related functional decline (Group 1; n = 274) and a case group with multimorbidity and functional limitations (Group 3; n = 100). Sarcopenia risk was assessed using the SARC-F questionnaire (threshold ≥ 4). A comprehensive geriatric battery—including the Barthel Index, FRAIL scale, MNA-SF, Pfeiffer test, SPPB, handgrip dynamometry, and IPAQ—characterised multidimensional vulnerability. Annual direct and indirect costs were estimated using unit costs from Spanish national health accounts, and intervention cost-effectiveness was modelled using published meta-analytic data. Results: Overall sarcopenia risk prevalence was 36.4% (n = 136; SARC-F ≥ 4), rising to 83.0% in the case group versus 19.3% in controls (OR ≈ 21.5, p < 0.001). Prevalence was 42.1% in males and 30.9% in females. Diabetes was independently associated with elevated risk (44.8% vs. 29.9%; OR 1.90, 95% CI 1.23–2.92; p = 0.003). Health Zone 1 exhibited the highest prevalence (63.0%) versus Zones 2 (23.5%) and 3 (32.8%). Multidimensional vulnerability was pervasive: 28.6% of participants were frail, 75.7% had nutritional compromise, 11.5% showed moderate cognitive impairment, and 89.8% reported low or no physical activity. The estimated annual socio-economic cost of sarcopenia in Tenerife is approximately EUR 88.9 million (Spain nationally: EUR 12.1 billion). Combined exercise–nutrition interventions yield cost-per-QALY ratios of EUR 3800–7000, far below Spain’s EUR 25,000/QALY threshold. Conclusions: Sarcopenia constitutes a major, multidimensionally compounded health burden in Tenerife’s older population, concentrated among frail, diabetic, nutritionally compromised, and physically inactive individuals. The economic case for universal SARC-F screening and multicomponent intervention is compelling, exceeding cost-effectiveness thresholds by a wide margin. Territorial disparities in burden call for equity-oriented, place-based resource allocation within the Canarian health system. Full article

In high-demand financial environments, employees’ capacity to regulate and sustain personal energy may constitute a critical yet underdeveloped organizational resource. Drawing on the Job Demands–Resources (JD-R) model and Conservation of Resources (COR) theory, this study conceptualizes energy management as a multidimensional personal resource that may support adaptive functioning and innovation under demanding work conditions. Despite increasing conceptual attention to energy-related constructs, systematic scale validation and cross-level performance evidence remain limited. This research adopts a two-study design to develop and validate a multidimensional Energy Management Scale within financial institutions. Study 1 (N = 299 employees from 11 financial institutions) examines the factorial structure, reliability, and nomological validity of the scale. Confirmatory factor analysis is used to examine the proposed four-dimensional configuration of physical, emotional, mental, and spiritual energy. The scale demonstrates acceptable internal consistency reliability and evidence of structural validity, including convergent and discriminant validity. Structural modeling results reveal that overall energy management is positively related to innovative behavior and organizational citizenship behavior. However, perceived workload was significantly associated only with physical energy, suggesting that demand-related mechanisms of energy may not operate uniformly across energy components. Additionally, exploratory institution-level aggregation analyses showed preliminary, counterintuitive negative associations between mean organizational energy levels and return on equity (ROE) in some years. Given the limited number of institutional clusters, these cross-level findings are preliminary and intended to provide initial external criterion evidence rather than confirmatory causal inference. Study 2 (N = 148 employees from two institutions) further examines alternative scale versions and external validity through stress coping capacity, job satisfaction, and life satisfaction. Results were discussed to examine the robustness and predictive validity of the scale across samples. Collectively, this study advances energy management research by providing a psychometrically supported measurement instrument and preliminary multilevel evidence of its organizational relevance. The findings position energy management as a measurable human-capital resource with implications for sustainable workforce innovation and performance in financial institutions. Full article

The built environment is the core material carrier shaping urban vitality, and its impact on urban vitality constitutes a key research hotspot in urban geography and urban–rural planning. Most existing studies focus on single cities and single scales. They pay insufficient attention to the heterogeneity of their relationship across different city types and spatial scales. They also lack a systematic framework for multi-dimensional comparative analysis. This study takes Chengdu and Chongqing as cases. They are the core cities of the Chengdu–Chongqing Twin-City Economic Circle. Three grid scales are applied. Using the XGBoost–SHAP-integrated model, this paper explores the differences in indicator importance, nonlinear impacts, and threshold effects of built environment on urban vitality. The objectives of this study are as follows: (1) This study will reveal the spatiotemporal differentiation characteristics and patterns of urban vitality across multiple cities, multiple grid scales, and multiple time periods. (2) This study will identify the relative importance of built environment indicators and their heterogeneous patterns across different cities and grid scales. (3) This study will clarify the nonlinear relationship between the built environment and urban vitality, as well as grid-scale differences and city differences. The results show the following: (1) Urban vitality exhibits significant distribution differences across cities, grid scales, and times. (2) In terms of relative importance, mean building height and building density are both important influencing indicators of urban vitality at multiple grid-scales in different cities. The effects of certain built environment indicators on urban vitality vary across cities and grid scales. Road intersection density plays a prominent role in Chengdu, while commercial accessibility has a significant influence in Chongqing. As the scale changes, indicators including road density, road intersection density, and commercial accessibility demonstrate distinct variation patterns. (3) The nonlinear effects of the built environment on urban vitality are significant and differ across cities and grid scales. The nonlinear effects of certain built environment indicators in Chongqing are more complex than those in Chengdu. As the scale changes, the nonlinear effect trends and thresholds of certain built environment indicators also show significant variations. Based on multi-city and multi-scale spatial analysis, this study deepens our systematic understanding of the relationship between the built environment and urban vitality. It provides a quantitative basis for understanding the interaction between human activities and physical spaces in different types of cities and at different grid scales. It also provides a referable paradigm for multi-dimensional analysis in similar studies. Full article

The pursuit of sustainable winter road maintenance has intensified the need for deicers that balance functional effectiveness, economic viability, and minimal environmental impact. However, the absence of a systematic, multi-dimensional evaluation framework has hindered informed product selection and green procurement. This study develops and validates the Comprehensive Deicer Multi-criteria Evaluation System (CDMES)—a structured assessment framework that integrates economic, functional, environmental, and infrastructural sustainability dimensions. The evaluation index system was constructed for deicers, consisting of 18 indicators including preparation cost, engineering maintenance cost, operability of agent preparation, application difficulty, asphalt binder adhesion loss, minimum application concentration, proportion of active ingredients, effective time, ambient temperature, freezing point, solid dissolution rate, relative snow/ice-melting capacity, seed damage rate, chlorophyll attenuation, soil pH, aqueous solution pH, steel–carbon corrosion rate, and pavement friction attenuation rate. Subsequently, the analytic hierarchy process (AHP) was employed to determine the weight of each indicator, and evaluation criteria were established in accordance with relevant standards and literature. Finally, this weight determination method, combined with the simple additive weighting (SAW) method for index aggregation, forms a quantitative evaluation model. These elements together constitute a comprehensive deicer evaluation system, designated as the Comprehensive Deicer Multi-criteria Evaluation System (CDMES). Validation using three representative deicers—sodium chloride, a composite chloride-based formulation, and an organic acetate-based product—demonstrated that the CDMES can effectively discriminate product performance across multiple sustainability dimensions and identify critical weaknesses that may be obscured by purely compensatory scoring. The framework offers a transparent and reproducible decision-support tool for winter maintenance managers seeking to align deicer selection with sustainability objectives. Full article

Constructing age-friendly residential environments is essential for supporting aging in place among the growing population of urban empty-nest older adults in China. Grounded in person–environment fit theory, this study developed and validated a multidimensional Aging-Suitability Index (ASI) to examine how residential environmental factors shape housing suitability and perceived independence. In this study, “aging suitability” refers to the degree of fit between residential environments and older adults’ needs for safety, functionality, accessibility, social support, and technological support, with the central aim of enabling aging in place and independent living. Questionnaire data were collected from 753 urban empty-nest older adults across 19 provinces in China and analyzed using partial least squares structural equation modeling (PLS-SEM). The structural model showed strong explanatory power (R² = 0.754). The results revealed a clear hierarchy of environmental influences. Safety facilities and physical design were the strongest direct predictors of residential aging suitability, indicating that risk reduction and ergonomically appropriate spatial design constitute the foundation of age-friendly housing. Although accessibility showed a smaller direct effect, it exerted a significant indirect effect through perceived independence, with 67.35% of its total effect mediated through this pathway, highlighting the importance of barrier-free design in maintaining autonomy. Social support and smart technology also contributed positively as complementary resources that strengthened person–environment fit. These findings suggest that age-friendly housing interventions should move beyond fragmented modifications toward integrated residential renewal strategies that prioritize safety and physical design, improve accessibility to support independent living, and combine community support with age-friendly technologies. This study provides empirical evidence to inform built-environment decision-making in the design and renewal of housing for older adults in rapidly aging urban contexts. Full article

In response to the bottleneck issue of natural rubber selection in aircraft tire formulation design, this study proposes a data-driven screening methodology that integrates a simulated performance database with grey system theory. A multidimensional performance simulation database was constructed, encompassing representative NR brands from six major global producing regions: Malaysia, Indonesia, Thailand, Vietnam, Hainan (China), and Yunnan (China). This repository encompasses critical metrics, including raw rubber constitution, molecular characteristics, and the static/dynamic mechanical behaviors of vulcanizates. Utilizing this foundation, a novel material selection protocol was formulated, grounded in a multi-objective weighted intelligent grey target decision framework. The Analytic Hierarchy Process (AHP) was applied to ascertain differentiated performance criteria and assign corresponding weights, specifically tailored to the functional necessities of distinct aircraft tire sections. To substantiate the model’s efficacy, the primary tire of the ubiquitous Boeing 737-800 served as a validation case. The optimal Natural Rubber (NR) grade identified by the algorithm was cross-referenced with the empirical expertise and engineering practices of premier global tire manufacturers, thereby confirming the framework’s robustness and predictive accuracy. Consequently, this investigation establishes a comprehensive intelligent decision-making architecture, spanning data construction to engineering deployment, offering a quantitative and referential pathway for NR material screening in aviation applications. Full article