Search Results (7,661)

Divinylisoprene rubber, a copolymer of butadiene and isoprene, is used as raw material for rubber technical products, combining isoprene rubber’s elasticity and butadiene rubber’s wear resistance. These properties depend quantitatively on the copolymer composition, which depends on the kinetics of its synthesis. This work aims to theoretically describe how the monomer mixture composition in the butadiene–isoprene copolymerization affects the activity of the TiCl₄–Al(i-C₄H₉)₃ catalytic system (expressed by active sites concentration) via kinetic modeling. This enables development of a reliable kinetic model for divinylisoprene rubber synthesis, predicting reaction rate, molecular weight, and composition, applicable to reactor design and process intensification. Active sites concentrations were calculated from experimental copolymerization rates and known chain propagation constants for various monomer compositions. Kinetic equations for active sites formation were based on mass-action law and Langmuir monomolecular adsorption theory. An analytical equation relating active sites concentration to monomer composition was derived, analyzed, and optimized with experimental data. The results show that monomer composition’s influence on active sites concentration is well described by a two-step kinetic model (physical adsorption followed by Ti–C bond formation), accounting for competitive adsorption: isoprene adsorbs more readily, while butadiene forms more stable active sites. Full article

Because artificially cemented granular (ACG) materials employ diverse combinations of aggregates and binders—including cemented soil, low-cement-content cemented sand and gravel (LCSG), and concrete—their stress–strain responses vary widely. In LCSG, the binder dosage is typically limited to 40–80 kg/m³ and the sand–gravel skeleton is often obtained directly from on-site or nearby excavation spoil, endowing the material with a markedly lower embodied carbon footprint and strong alignment with current low-carbon, green-construction objectives. Yet, such heterogeneity makes a single material-specific constitutive model inadequate for predicting the mechanical behavior of other ACG variants, thereby constraining broader applications in dam construction and foundation reinforcement. This study systematically summarizes and analyzes the stress–strain and volumetric strain–axial strain characteristics of ACG materials under conventional triaxial conditions. Generalized hyperbolic and parabolic equations are employed to describe these two families of curves, and closed-form expressions are proposed for key mechanical indices—peak strength, elastic modulus, and shear dilation behavior. Building on generalized plasticity theory, we derive the plastic flow direction vector, loading direction vector, and plastic modulus, and develop a concise, transferable elastoplastic model suitable for the full spectrum of ACG materials. Validation against triaxial data for rock-fill materials, LCSG, and cemented coal–gangue backfill shows that the model reproduces the stress and deformation paths of each material class with high accuracy. Quantitative evaluation of the peak values indicates that the proposed constitutive model predicts peak deviatoric stress with an error of 1.36% and peak volumetric strain with an error of 3.78%. The corresponding coefficients of determination R² between the predicted and measured values are 0.997 for peak stress and 0.987 for peak volumetric strain, demonstrating the excellent engineering accuracy of the proposed model. The results provide a unified theoretical basis for deploying ACG—particularly its low-cement, locally sourced variants—in low-carbon dam construction, foundation rehabilitation, and other sustainable civil engineering projects. Full article

Improving occupational health and safety (OHS) in the construction industry can contribute to the advancement of the Sustainable Development Goals (SDGs), particularly Goals 3 (Good Health and Well-being) and 8 (Decent Work and Economic Growth). Yet, workers’ risk-taking behaviors (RTBs) remain a persistent challenge. Drawing on Social Cognitive Theory and Social Information Processing Theory, this study develops and tests a social influence model to examine how foremen’s safety attitudes (SAs) shape workers’ RTBs. Drawing on survey data from 301 construction workers in China, structural equation modeling reveals that foremen’s SAs significantly and negatively predict workers’ RTBs. However, the three dimensions of SAs—cognitive, affective, and behavioral—exert their influence through different pathways. Risk perception (RP) plays a key mediating role, particularly for the cognitive and behavioral dimensions. Furthermore, interpersonal trust (IPT) functions as a significant moderator in some of these relationships. By identifying the micro-social pathways that link foremen’s attitudes to workers’ safety behaviors, this study offers a testable theoretical framework for implementing the Sustainable Development Goals (particularly Goals 3 and 8) at the frontline workplace level. The findings provide empirical support for organizations to move beyond rule-based management and instead build more resilient OHS governance systems by systematically cultivating the multidimensional attitudes of frontline leaders. Full article

With the increasing application of digital interactive installations in museums, their role in enhancing audience engagement and cultural dissemination effectiveness has become prominent. However, ensuring the sustained use of these technologies remains challenging. Based on distributed cognition and perceived value theories, this study investigates key factors influencing users’ continuous usage of digital interactive installations using the Capital Museum in Beijing as a case study. A theoretical model was constructed and empirically validated through Bayesian Structural Equation Modeling (Bayesian-SEM) with 352 valid samples. The findings reveal that perceived ease of use plays a critical direct predictive role in continuous usage intention. Environmental factors and peer interaction indirectly influence user behavior through learner engagement, while user satisfaction serves as a core mediator between perceived ease of use and continuous usage intention. Notably, perceived usefulness and entertainment showed no direct effects, indicating that convenience and social experience outweigh functional benefits in this context. These findings emphasize the importance of optimizing interface design, fostering collaborative environments, and enhancing user satisfaction to promote sustained participation. This study provides practical insights for aligning digital innovation with audience needs in museums, thereby supporting the sustainable integration of technology in cultural heritage education and preservation. Full article

According to the literature, the advancement of information and communication technology (ICT) has increased individual exposure to scams, turning fraud victimization into a significant concern. While prior research has primarily focused on socio-demographic predictors of fraud victimization, this study adopts a behavioral perspective that is grounded in the Signal Detection Theory (SDT) to investigate the likelihood determinants of individuals becoming fraud victims. Using survey data of 671 Indonesian respondents analyzed with the Partial Least Squares Structural Equation Modeling (PLS-SEM), we explored the roles of vigilance and financial literacy in moderating the relationship between fraud exposure and victimization. Our findings substantiate the notion that higher exposure to fraudulent activity significantly increases the likelihood of victimization. The results also show that vigilance negatively moderates the relationship between fraud exposure and fraud victimization, suggesting that individuals with higher vigilance are better at identifying scams, thereby decreasing their likelihood of becoming fraud victims. Furthermore, financial literacy is positively related to vigilance, indicating that financially literate individuals are more aware of potential scams. However, the predictive power of financial literacy on vigilance is relatively low. Hence, while literacy helps a person sharpen their indicators for detecting fraud, psychological, behavioral, and contextual factors may also affect their vigilance and decision-making. Full article

Introduction: The main purpose of this study was to test a hierarchical model of motivation that integrates Achievement Goal Theory and Self-Determination Theory to explain and predict exercise adherence. Method: In total, 2180 exercisers (1020 female, 1160 male) aged between 18 and 60 years, from different gyms and health clubs, completed several scales validated in exercise settings, regarding perceived motivational climate, basic psychological need satisfaction, behavioral regulation, and exercise adherence. For the last measure, weekly computer access to a control system over a 6-month period before and after data collection was consulted. Results: Through structural equation models (SEM), it was verified that (1) task-involving climate positively predicted basic psychological needs. In turn, the satisfaction of these needs predicted autonomous motivation, which led to a positive prediction of adherence; (2) a small variation in exercise adherence was explained by the motivational model under analysis. Nevertheless, models significantly improved their analytical power when past adherence was inserted in the model increasing the explained variance in future behavior from 9.2% to 64%. Conclusions: In conclusion, autonomous motivation can predict people’s exercise adherence, and past behavior increases that predictive effect. The present study brings scientific evidence to the popular saying “tell me what you’ve done and, and I’ll predict what you’ll do”. Full article

Cellulose acetate (CA), commercially produced from natural cellulose, is one of the promising candidates to solve the microplastic issue. In this study, attempts were made to prepare CA microparticles by means of melt extrusion of incompatible polymer blends comprising CA with plasticizer (triacetin (TA)) and polyvinyl alcohol (PVA) followed by selective removable of TA and PVA. As implied by semi-theoretical equation previously established by Wu (Wu’s equation), particle size decreased with increasing shear rate or decreasing viscosity ratio of polymers. CA microparticles with a controlled size of 2–8 μm, narrow particle size distribution, and smooth surface were successfully obtained. Efforts were made to determine the numerical solution of Wu’s equation to compare them with observed particle size. To this end, interfacial tension between dispersed and matrix phases to be incorporated in the equation was determined by group contribution methods. The root mean squared error (RMSE) between the observed and calculated particle size was unsatisfactorily large, 4.46 μm. It was found that one of the possible reasons for the limited prediction accuracy was migration of TA from the dispersed to matrix phase affecting the viscosity ratio. Further efforts will be required to achieve a better prediction. Full article

In order to study the problem of obvious wall thinning in the wellbore caused by proppant backflow and sand production under throttling conditions in tight gas wells. Based on the gas-phase control equation, particle motion equation, and erosion model, the wellbore erosion model is established. The distribution law of pressure, temperature, and velocity trace fields under throttling conditions is analyzed, and the influences of different throttling pressures, particle diameters, and particle mass flows on wellbore erosion are analyzed. The flow field at the nozzle changes drastically, and there is an obvious pressure drop, temperature drop, and velocity rise. When the surrounding gas is completely mixed, the physical quantity gradually stabilizes. The erosion shape of the wellbore outlet wall has a point-like distribution. The closer to the throttle valve outlet, the more intense the erosion point distribution is. Increasing the inlet pressure and particle mass flow rate will increase the maximum erosion rate, and increasing the particle diameter will reduce the maximum erosion rate. The particle mass flow rate has the greatest impact on the maximum erosion rate, followed by the particle diameter. The erosion trend was predicted using multiple regression model fitting of the linear interaction term. The research results can provide a reference for the application of downhole throttling technology and wellbore integrity in tight gas exploitation. Full article

The constitutive model is widely employed to characterize the rheological properties of metallic materials under high-temperature conditions. It is typically derived from a series of high-temperature tests conducted at varying deformation temperatures, strain rates, and strains, including hot stretching, hot compression, separated Hopkinson pressure bar testing, and hot torsion. The original experimental data used for establishing the constitutive model serves as the foundation for developing phenomenological models such as Arrhenius and Johnson–Cook models, as well as physical-based models like Zerilli–Armstrong or machine learning-based constitutive models. The resulting constitutive equations are integrated into finite element analysis software such as Abaqus, Ansys, and Deform to create custom programs that predict the distributions of stress, strain rate, and temperature in materials during processes such as cutting, stamping, forging, and others. By adhering to these methodologies, we can optimize parameters related to metal processing technology; this helps to prevent forming defects while minimizing the waste of consumables and reducing costs. This study provides a comprehensive overview of commonly utilized experimental equipment and methods for developing constitutive models. It discusses various types of constitutive models along with their modifications and applications. Additionally, it reviews recent research advancements in this field while anticipating future trends concerning the development of constitutive models for high-temperature deformation processes involving metallic materials. Full article

The combined application of fibers and lightweight aggregates (LWAs) represents an effective approach to achieving high-strength, lightweight concrete. To enhance the predictability of the mechanical properties of fiber-reinforced lightweight aggregate concrete (LWAC), this study conducts an in-depth investigation into its hydration characteristics. In this study, high-strength LWAC was developed by incorporating low water absorption LWAs, various volume fractions of basalt fiber (BF) (0.1%, 0.2%, and 0.3%), and a ternary cementitious system consisting of 70% cement, 20% fly ash, and 10% silica fume. The hydration-related properties were evaluated through isothermal calorimetry test and high-temperature calcination test. The results indicate that incorporating 0.1–0.3% fibers into the cementitious system delays the early hydration process, with a reduced peak heat release rate and a delayed peak heat release time compared to the control group. However, fitting the cumulative heat release over a 72-h period using the Knudsen equation suggests that BF has a minor impact on the final degree of hydration, with the difference in maximum heat release not exceeding 3%. Additionally, the calculation model for the final degree of hydration in the ternary binding system was also revised based on the maximum heat release at different water-to-binder ratios. The results for chemically bound water content show that compared with the pre-wetted LWA group, under identical net water content conditions, the non-pre-wetted LWA group exhibits a significant reduction at three days, with a decrease of 28.8%; while under identical total water content conditions it shows maximum reduction at ninety days with a decrease of 5%. This indicates that pre-wetted LWAs help maintain an effective water-to-binder ratio and facilitate continuous advancement in long-term hydration reactions. Based on these results, influence coefficients related to LWAs for both final degree of hydration and hydration rate were integrated into calculation models for degrees of hydration. Ultimately, this study verified reliability of strength prediction models based on degrees of hydration. Full article

Identifying predictors of pro-environmental behaviors (PEBs) can not only figure out who concerns about the environment most but also inform possible pathways that advance or inhabit such prosocial actions. Most past studies and theories focus on factors that reside within personal characteristics or sociopsychological mechanisms rather than taking a holistic view that integrates these two elements into a framework. This study investigates how socioeconomic status (SES) correlates with PEBs, integrating both structural and psychological mechanisms. Drawing on the Stimulus–Organism–Response (SOR) theoretical framework, this paper examines the paradox whereby individuals with higher SES exhibit more frequent environmental actions yet demonstrate lower willingness to pay (WTP)—a form of economic sacrifice. Using nationally representative data from the 2021 Chinese General Social Survey (CGSS), our structural equation modeling reveals that adulthood SES positively correlates with environmental values and behaviors but negatively correlates with WTP. This challenges the traditional linear assumption that greater willingness necessarily leads to greater action. Additionally, while childhood SES predicts adult SES, it shows no direct effect on environmental engagement. These findings highlight multidimensional pathways by which SES shape environmental actions, necessitating differentiated policy approaches to build a sustainable world. Full article

Background: It is well-established that, for adolescents to adopt sustainable healthy lifestyle behaviors, not only access to information but also the skills required to translate that information into action are critical. In this field, research that examines the relationship between e-health literacy and sustainable healthy lifestyle behaviors within the context of physical literacy is notably scarce. In this context, the aim of this study is to examine the effect of e-health literacy on a sustainable healthy lifestyle and to evaluate the mediating role of physical literacy in this relationship. Methods: A total of 835 adolescents from high schools across Türkiye voluntarily participated in this study. During the data collection process, the e-Health Literacy Scale, the Perceived Physical Literacy Scale, and the Healthy and Sustainable Lifestyle Scale were utilized. Data were analyzed using the JASP (version 0.18.3.0) software. Correlation analysis and structural equation modeling were conducted, and the bootstrap method (n = 5000) was employed for mediation analysis. Results: The effect of e-health literacy on a sustainable healthy lifestyle was found to be positive and statistically significant (β = 0.452, p < 0.001). Similarly, e-health literacy significantly predicted physical literacy (β = 0.755, p < 0.001), and physical literacy significantly predicted a sustainable healthy lifestyle (β = 0.310, p < 0.001). The mediating effect was also statistically significant (β = 0.234, p < 0.001). The model explained 32% of the variance in healthy lifestyle behaviors. Conclusions: The findings indicate that evaluating e-health literacy and physical literacy together provides a holistic approach to fostering sustainable healthy lifestyle habits among adolescents. It is recommended that intervention programs be structured to encompass both areas of competence. Full article

Urban subsurface pipeline bursts can induce catastrophic cascading effects, including ground collapse, infrastructure failure, and socioeconomic losses. However, stratum responses during the erosion cavity expansion phase and corresponding disaster mitigation strategies have rarely been researched. In this study, a numerical model validated through experimental tests was employed to investigate the effects of internal water pressures, burial depths, and different geotextile-based disaster mitigation strategies. It was revealed that a burial depth-dependent critical internal water pressure governed the erosion cavity expansion, and a predictive equation was derived based on the limit equilibrium theory. Higher internal water pressure accelerated the erosion cavity expansion and amplified the stratum stress within a range of twice the diameter D. Increased burial depth $d$ reduced peak ground heave but linearly expanded the heave zone range, concurrently elevating the overall stratum stress level and generating larger stress reduction zones (i.e., when $d/D$ = 3.0, the range of the stress reduction zone was 8.0D). All geotextile layout configurations exhibited different disaster mitigation effects (the peak ground heave was reduced by at least 15%). The semi-circular closely fitted configuration (SCCF) optimally restricted the expansion of the erosion cavity, reduced the stratum displacement (i.e., 39% reduction in the peak ground heave), and avoided stress concentration. Comprehensive analysis indicated that SCCF was suited for low-pressure pipelines in deformation-sensitive stratum and semi-circular configuration (SC) was suitable for deformation-insensitive pipeline sections. These findings provide actionable insights for tailoring mitigation strategies to specific operational risks. Full article

Earthquakes can severely disrupt power distribution networks, causing extensive outages and disconnection from the transmission grid. This paper proposes a two-stage restoration method tailored for post-earthquake distribution systems. First, earthquake-induced damage is modeled using ground motion prediction equations (GMPEs) and fragility curves, and degraded network topologies are generated by Monte Carlo simulation. Then, a time-domain generator start-up model is developed as a mixed-integer linear program (MILP), incorporating cranking power and radial topology constraints. Further, a prioritized load recovery model is formulated as a mixed-integer second-order cone program (MISOCP), integrating power flow, voltage, and current constraints. Finally, case studies demonstrate the effectiveness and general applicability of the proposed method, confirming its capability to support resilient and adaptive distribution network restoration under various earthquake scenarios. Full article

The current study explores the changes in beef quality following partial freezing and during superchilled storage, alongside chilled storage comparisons. Kinetic models were developed to predict changes in colour difference (∆E), thiobarbituric acid−reactive substances (TBARS), total volatile basic nitrogen (TVB−N), drip loss and firmness. Beef samples were partially frozen in an air blast freezer at −30 °C for 9 min prior to storage at −5 °C, −4 °C, −2.8 °C, −1.8 °C. Chilled beef samples were directly stored at 2 °C and 6 °C without partial freezing. All samples were stored for 21 days. The lightness (L*), redness (a*), yellowness (b*) and colour difference (∆E) were significantly lower in superchilled storage samples compared to chilled storage samples. The pH of beef samples increased gradually over time (p < 0.05). TBARS, TVB−N and drip loss increased while firmness decreased with the increase in storage time in both storage conditions (p < 0.05). Overall, beef quality was affected by both storage duration and temperature. Firmness followed the first order kinetic model; drip loss, TVB−N, TBARS and colour difference (∆E) fitted the zero−order kinetic model. Temperature dependence was adequately modelled using Arrhenius−type equation with the activation energy values of 110.111, 52.870, 68.553, 119.480, 47.301 kJ/mol for drip loss, firmness, TBARS, TVB−N and colour difference (∆E), respectively. The models demonstrated strong predictive performance, with RMSE and MAPE values within ±10%. The developed kinetic models successfully predicted quality changes within the −5 °C to 6 °C temperature range. Full article