西安交通工程学院

This study explores the optimization of educational resource allocation using 6G network slicing and artificial intelligence technology. With the rapid advancement of 6G and AI, educational resources can be dynamically allocated to ensure efficient and real-time processes in multimedia services, cloud computing, and IoT applications. AI monitors resource usage, adjusting allocations to reduce network congestion and resource waste. Experimental results show a 25

Understanding how transport conditions and the built environment shape urban CO2 emissions is critical for low-carbon urban development. This study analyses CO2 emission intensity across fifty major Chinese cities using integrated ODIAC emissions, VIIRS night-time lights, traffic performance indicators, built-environment morphology, population/POI structure, and socioeconomic controls. We develop a GeoAI workflow that couples XGBoost modelling with SHAP interpretation, congestion-based city grouping, and 1 km grid-level GNNWR to map intra-urban spatial non-stationarity. The global model identifies night-time light intensity as the strongest predictor, followed by population density and building density. SHAP results reveal pronounced nonlinearities, with high sensitivity at low–medium levels and diminishing marginal effects as activity and density increase. Although transport indicators are less influential in the aggregate model, their roles differ across congestion regimes: in low-congestion cities, emissions align more consistently with overall activity intensity, whereas in high-congestion cities they respond more strongly to population distribution, motorisation, and built-form intensity, with less stable relationships. Grid-level GNNWR further shows that key mechanisms are spatially uneven within cities, with local effects concentrating in specific cores and corridors or fragmenting across multiple subareas. These findings demonstrate that emission drivers are context-dependent across and within cities. Accordingly, uncongested cities may gain more from activity-related energy-efficiency measures, while highly congested cities may require congestion-sensitive land-use planning, spatial-structure optimisation, and motorisation control. Integrating explainable GeoAI with regime differentiation and spatial heterogeneity mapping provides actionable evidence for targeted low-carbon planning.

With rising climate risks, how firms respond through financial decisions has drawn increasing attention. Using Chinese A-share listed firms from 2007 to 2022, this study examines the effect of climate risk on firms’ dynamic capital structure adjustment. The results show that climate risk significantly accelerates adjustment toward target leverage. Mechanism analyses indicate that digital and green innovation strengthen this effect by facilitating firms’ proactive adaptation to climate challenges. Subsample tests reveal that climate transition risk, manifested through environmental regulation, carbon-reduction targets, and technological standards, is the primary driver of capital structure adjustment, while serious and chronic physical risks are insignificant. These results highlight the pathway of“climate risk—innovation response—capital structure adjustment,”enriching the literature on the economic consequences of climate risk and capital structure dynamics.The study also provides theoretical insights and practical implications for firms seeking to optimize capital structure under climate challenges.

Thermal performance of phase change processes in a sidewall-heated rectangular cavity with non-contact metal fin was experimentally and numerically investigated in detail. In contrast to the contacting fin design, the non-contact fin design removes the requirement of connecting the fin to the heat source and consequently prevents contact thermal resistance. Natural convection caused by temperature difference leads to heat accumulation in the upper region of cavity and establishes a distinct thermal stratification, resulting in an insufficiently melted dead zone. A non-contact metal fin enables the transfer of heat from the high-temperature fluid to the bottom dead zone. The results indicated that the phase change thermal storage unit with an aspect ratio of 1:1.1, a dimensionless fin height of 1 and a dimensionless fin position of 1/6 achieves the best heat transfer performance. It can reduce melting time by 16.7 % and increases the heat transfer rate by 13.6 % when it is compared to a non-fin structure. Furthermore, for the Stefan number from 0.17 to 0.46, a 250.2 % increase in the average heat transfer rate is achieved, along with a 66.5 % drop in melting time. Finally, an experimental correlation of Nusselt number and RaSte number is established to provide guidance for the optimal design of the phase change thermal storage unit with non-contact fin.

The purpose of this study is to characterize the thermal performance of a novel cross-arranged fin latent heat thermal energy storage (LHTES) system through experiments. The analysis encompasses illustrating changes in the melting front over time and examining the impact of varying Stefan numbers (Ste) and Reynolds numbers (Re) on the melting progression. The cross-arranged fin type LHTES units promote uniform heat distribution, increase melting rates in multiple directions, and thus improve the non-uniformity of heat transfer. Therefore, compared with the longitudinal fin LHTES device, the melting time has been reduced by a maximum of 10.7 %. However, for the Ste number of 0.42, the melting time of the longitudinal fin LHTES unit is very close to that of the cross-arranged fins unit. The energy efficiency ratio of the new LHTES device was also calculated at different Ste and Re numbers, indicating that as the Ste number increases and the Re number decreases, the energy efficiency ratio will increase. For the intermittent heating experiment, intermittent heating significantly affected the thermal performance of the unit, balanced the heating rate in different phase change material (PCM) regions, and produced a consistent temperature distribution.