The environmentally responsible behavior (ERB) of visitors within forested national parks is critical for balancing biodiversity conservation and sustainable recreation. While the Value-Belief-Norm (VBN) model has been widely used to explain ERB, it has rarely incorporated context-specific value perceptions, such as assigned value. This study extends the VBN model by integrating this construct and examines its role in shaping visitors' pro-environmental intentions. Taking Qianjiangyuan National Park in China as a case study, we incorporate visitors' perception of the social value derived from the park's forest-based ecosystem services into an expanded VBN framework. Data were analyzed using partial least squares structural equation modeling. The results show that assigned value positively influences ERB intention; pro-environmental personal norms are the strongest direct predictor (beta = 0.426); and biospheric value, egoistic value, and personal norms significantly foster assigned value formation, whereas altruistic value shows no significant effect. These findings highlight the importance of integrating situational, forest-specific value perceptions into behavioral models and offer management insights for promoting ERB intention through value-congruent communication in forest recreation settings.
The structural and electrical characteristics of Cu-doped LiGaCr4O8 ceramics were explored. X-ray diffraction analysis of the samples indicated changes in the Cr-Cr bond lengths and Cr-O-Cr bond angles. The distorted CrO6 octahedra caused by doping affected the dielectric and piezoelectric properties. The dielectric properties were explored in detail, and the variations of the permittivity and loss with frequency were accurately measured from 20 Hz to 10 MHz at a range of temperatures. Cu doping enhanced the dielectric constant by approximately one order of magnitude while reducing the dielectric loss by nearly two orders of magnitude. The frequency-dependent electrical modulus showed non-Debye type relaxation behavior. Within the temperature measurement range, the samples exhibited both positive temperature coefficient of resistance and negative temperature coefficient of resistance characteristics. The variation in DC resistivity followed the Arrhenius equation. The activation energy of DC resistivity estimated using the Arrhenius equation exhibits a nonlinear trend. As the amount of Cu doping increased, the piezoelectric charge coefficients increased.
Considering the overall performance of public transportation systems is crucial for evaluating a system and is essential for accurately assessing the accessibility of the system. However, most previous studies have measured accessibility from the perspective of stations. Only a few studies have addressed accessibility and its spatial heterogeneity from the route perspective. To fill these gaps, this paper explores the construction and validation of a route-level accessibility measure. First, this study proposes a route-level accessibility measure that holistically evaluates the accessibility level of public transit systems from a route perspective. Second, the proposed measure is applied to assess the accessibility of bus and metro in Beijing, the two most widely used modes in the existing public transit system. Finally, the proposed measure is compared with other route-level accessibility measures from the literature. Machine learning models are used to explore the nonlinear relationship between these accessibility outcomes and land prices. The proposed measure is then validated by comparing its evaluation performance with other methods. The results of the three performance evaluation metrics, namely, R2, root-mean-square error, and relative importance, indicate that the proposed measure outperformed the existing route-level accessibility measure. The proposed measure exhibits stronger predictive power for land prices compared with the existing route-level accessibility measure in the literature. By measuring the accessibility of public transit systems from a route perspective, this study complements the exploration of route-level accessibility measures in the research field, helping planners rationally evaluate the coverage level of urban public transit networks.
Hydrothermally deposited Sb2(S,Se)3 is a promising absorber for solution-processed thin-film solar cells, yet its post-treatment typically requires high-temperature annealing (approximate to 370 degrees C), which inevitably causes severe selenium loss. This loss generates a compositionally disordered near-surface region and degrades device performance. Here, we develop a simple PbBr2-assisted approach in which an in-situ formed Pb(SxSe1-x) nanoparticle film initiates Sb2(S,Se)3 crystallization at a substantially lower temperature. The nanoparticle film is shown to direct the microstructural evolution by accelerating grain coalescence and inducing (hk1)-preferred crystallinity, producing a denser and flatter absorber with markedly suppressed selenium loss and reduced surface oxidation. As a result, the champion PbBr2-treated device delivers a PCE of 10.51%, representing a 16.8% improvement over the 9.00% control, mainly arising from enhanced surface selenium retention and improved interfacial band alignment as supported by compositional and electronic analyses. This work offers a practical materials-engineering strategy for Sb2(S,Se)3 photovoltaics that resolves the long-standing trade-off between high-temperature crystallization and selenium loss, providing a pathway to stabilize surface composition while maintaining a high-quality junction for higher device efficiency.
The stochastic FitzHugh-Nagumo (FHN) equation is a fundamental model for excitable media, widely used to describe neuronal signal transmission and population dynamics under random perturbations. However, analytical studies that simultaneously incorporate stochastic effects, nonlinear wave propagation, and bifurcation behavior are still limited. In this work, we investigated a stochastic FHN model with multiplicative Gaussian noise and developed a unified analytical framework by integrating the unified method with a novel auxiliary equation technique. Using a stochastic transformation and expectation operator, the governing stochastic partial differential equation was reduced to a deterministic traveling-wave ordinary differential equation. This framework enables the systematic derivation of multiple classes of exact solutions, including rational, trigonometric, and hyperbolic soliton structures such as kink, anti-kink, periodic, and singular waves. Compared with existing methods, the proposed approach provides a more general mechanism for constructing diverse solution families within a single analytical structure. Furthermore, the reduced equation was reformulated into a planar dynamical system via a Galilean transformation, allowing bifurcation and phase-portrait analysis. Graphical results clearly illustrate the influence of noise intensity on wave morphology and temporal dynamics. The findings provide new analytical insights into noise-modulated excitation phenomena in stochastic nonlinear systems.
