Guizhou Institute of Technology

ABSTRACT Climate change profoundly influences local microclimates, and plant transpiration processes are directly regulated by these microclimatic conditions. As a key topographic factor, mountain slope aspects shape local microclimatic characteristics through the redistribution of hydrothermal resources. Although plant growth and physiological processes are more directly influenced by local microclimates than by macroclimates, the differentiated responses of plant transpiration dynamics to environmental factors across different slope aspects and their underlying driving mechanisms remain unclear. This study investigates Zanthoxylum bungeanum forests on sunny and shady slopes at the same altitude in plateau gorges within a subtropical monsoon climate zone. Through in situ monitoring of sap flow (SF), local meteorological factors, soil water content (SWC) and stable isotope composition, we explored the effects of differences in microclimate and SWC on plant transpiration and water use strategies. The results showed that: (1) Water use patterns exhibited significant seasonal and slope‐related differences. During the rainy season, plants on both slopes primarily relied on shallow soil water. In the dry season, plants on the shady slope consistently utilised deep soil water (30–60 cm), whereas plants on the sunny slope rapidly shifted to using shallow and intermediate water sources following light rainfall, facing a higher risk of water source depletion. (2) During both dry and rainy seasons, SF on both slopes was primarily driven by vapour pressure deficit (VPD) and air temperature (Ta), which exerted threshold control effects on SF. These thresholds varied with slope aspect and season. Specifically, the VPD threshold during the rainy season was sunny slope (2.7 kPa) < shady slope (3.2 kPa); during the dry season, it was sunny slope (31.9°C) > shady slope (30.1°C). The Ta threshold during the rainy season was sunny slope (34.3°C) < shady slope (38.4°C); during the dry season, it was sunny slope (31.9°C) > shady slope (30.1°C). Furthermore, the stomatal conductance of plants on the shady slope was more sensitive to changes in VPD and Ta than that of plants on the sunny slope. Therefore, under drought conditions, plants on the shady slope exhibited a more robust water use strategy, with greater stability in transpiration and stomatal regulation, significantly reducing the risk of hydraulic dysfunction and demonstrating stronger drought adaptability compared to plants on the sunny slope.

Traffic flow forecasting is crucial for effective urban planning and the development of intelligent transportation systems. However, accurately capturing the complex spatiotemporal dependencies in traffic flow data remains a significant challenge. Current approaches typically face two major limitations: (i) insufficient modeling of long-term historical traffic flow patterns, which hinders the capture of global trends and periodic behaviors; and (ii) inadequate consideration of spatial structures and temporal response heterogeneity, which limits the model’s representational capacity. To tackle these challenges, this paper proposes a novel forecasting framework named Spatiotemporal Memory Decoupled Transformer (STMDFormer). First, a spatiotemporal embedding module is designed to fuse topological node structures with multi-scale periodic information. Then, a spatial memory attention mechanism is introduced, incorporating a learnable historical memory bank and a biased adjacency matrix for dynamic modeling of long-term traffic flow patterns. Furthermore, a decoupled learning module is designed to separate spatial and temporal features through normalization techniques, while employing multi-head attention to better capture spatiotemporal heterogeneity. Extensive experiments on four real-world traffic datasets demonstrate that STMDFormer consistently outperforms various state-of-the-art baselines in forecasting accuracy, validating its effectiveness in dynamic spatiotemporal modeling.

To investigate the effects of milling methods on the quality performance of millet dumplings from the perspective of starch hierarchical structural changes, different milling methods (dry, semi-dry and wet milling) were compared. Results indicated that semidry milling millet flour had lower amount of damaged starch (3.71%) and freezable water compared with dry milling flour, but higher than wet milling. Starch granules prepared by wet milling had the highest values of lamellar ordering degree ( d c , 6.16 nm), relative crystallinity (20.6%), short-range ordered degree (0.97) and double helices (42.5%). And these ordered multi-scale structures may increase the thermostability and characteristic viscosity of starch, thus leading to a decreased water loss rate, as well as elevations in the transmittance of the soup, hardness, adhesiveness and gumminess of millet dumplings. These indicated that wet-milled millet flour with reduced content of damaged starch and highly ordered hierarchical structure may facilitate the production of dumplings with superior quality. • Proso millet milled with different methods were used for preparing dumplings. • Millet flours with damaged starch content below 4% were suitable for sweet dumpling. • The relationship among structure, characteristics and product quality was revealed. • Highly ordered structures may favor the production of dumplings with superior quality.