A new species of Hypodematium (Hypodematiaceae) from China

Volume: 92Start Page: 37End Page: 4

STUDIES ON THE SEED-LIKE FRUITS OF SUB-GENUS SCLAREA OF SALVIA OF LABIATAE IN CHINA

The macro-morphology and the ultrastructure ornamentation of seed-like fruits of four Sections, Sect. Drymosphace, Sect. Aethiopis, Sect. Plethiosphace and Sect. Notiosphace (comprising 14 species) of the Sub-genus Sclarea of Salvia of Labiatae in China were systematically studied by using scanning electron microscope. Their characteristics were recorded as plain, stripes, reticulate, convex meshes to reticulate and convex meshes, and both reticulate and convex meshes appeared on dorsal and ventral surfaces of seed-like fruits of one species at the same time. The plain type was an original type; the stripes, reticulate and convex meshes were intermediate types; and both reticulate and convex meshes appeared on seed-like fruits of one species was regarded as an evolved type. They had intraspecific stabilities, but significant interspecific differences in both the macro-morphological features and the ultrastructure ornamentation, which provided evidences for their classification and identification. Fifty six photographs of the seed-like fruits of 14 species of the subgenus collected by scanning electron microscope have been attached

Modeling for Predicting the Potential Geographical Distribution of Three <i>Ephedra</i> Herbs in China

Ephedra species are beneficial for environmental protection in desert and grassland ecosystems. They have high ecological, medicinal, and economic value. To strengthen the protection of the sustainable development of Ephedra, we used occurrence records of Ephedra sinica Stapf., Ephedra intermedia Schrenk et C.A. Mey., and Ephedra equisetina Bge., combined with climate, soil, and topographic factors to simulate the suitable habitat of three Ephedra based on ensemble models on the Biomod2 platform. The results of the models were tested using AUC, TSS, and kappa coefficients. The results demonstrated that the ensemble model was able to accurately predict the potential distributions of E. sinica, E. intermedia, and E. equisetina. Eastern and central Inner Mongolia, middle and eastern Gansu, and northeastern Xinjiang were the optimum regions for the growth of E. sinica, E. intermedia, and E. equisetina, respectively. Additionally, several key environmental factors had a significant influence on the suitable habitats of the three Ephedra. The key factors affecting the distribution of E. sinica, E. intermedia, and E. equisetina were annual average precipitation, altitude, and vapor pressure, respectively. In conclusion, the results showed that the suitable ranges of the three Ephedra were mainly in Northwest China and that topography and climate were the primary influencing factors

Parking and Ride Induction Methods for Drivers in Commuting Scenes

Parking and ride is a very effective method to improve the traffic condition of commuter channels, and it is necessary to develop effective parking guidance strategies. In this study, considering the travel time, walking distance, parking cruise time, parking fee, and personal attributes of drivers, a probability model of parking and ride selection in commuter scenarios was proposed, and a dynamic price adjustment method based on the equilibrium of parking occupancy in the region was constructed. The parking price was adjusted by determining the target occupancy, thus affecting the parking choice behavior to guide the commuter to park. The example analysis showed that this method adjusted the selection probability of the parking lot by using the dynamic price adjustment method from the perspective of regional parking occupancy equilibrium, solved the model by symmetric duality algorithm and formulated a reasonable parking replacement induction scheme to achieve the goal of occupancy equilibrium. Compared with parking guidance under static pricing, it can avoid the crowding of commuter vehicles into the city center effectively to reduce the congestion of commuter channels

Analyzing Commute Mode Choice Using the LCNL Model in the Post-COVID-19 Era: Evidence from China

The purpose of this paper is to gain an insight into commuting and travel mode choices in the post-COVID-19 era. The surveys are divided into two waves in Qingdao, China: the first-wave questionnaires were collected under the background of a three-month zero growth of cases; the second wave was implemented after the new confirmed cases of COVID-19. The latent class nested logit (LCNL) model is applied to capture heterogeneous characteristics among the various classes. The results indicate that age, income, household composition, and the frequency of use of travel modes are latent factors that impact users&rsquo; attitudes toward mass transit and the private car nests when undergoing the shock of the COVID-19 pandemic. Individuals&rsquo; trepidation regarding health risks began to fade, but this is still a vital consideration in terms of mode choice and the purchase of vehicles. Moreover, economic reinvigoration, the increase in car ownership, and an increase in the desire to purchase a car may result in great challenges for urban traffic networks

Parking and Ride Induction Methods for Drivers in Commuting Scenes

Parking and ride is a very effective method to improve the traffic condition of commuter channels, and it is necessary to develop effective parking guidance strategies. In this study, considering the travel time, walking distance, parking cruise time, parking fee, and personal attributes of drivers, a probability model of parking and ride selection in commuter scenarios was proposed, and a dynamic price adjustment method based on the equilibrium of parking occupancy in the region was constructed. The parking price was adjusted by determining the target occupancy, thus affecting the parking choice behavior to guide the commuter to park. The example analysis showed that this method adjusted the selection probability of the parking lot by using the dynamic price adjustment method from the perspective of regional parking occupancy equilibrium, solved the model by symmetric duality algorithm and formulated a reasonable parking replacement induction scheme to achieve the goal of occupancy equilibrium. Compared with parking guidance under static pricing, it can avoid the crowding of commuter vehicles into the city center effectively to reduce the congestion of commuter channels

Spatial distribution dynamics for Epimedium brevicornum Maxim. from 1970 to 2020

Abstract At different time scales, a species will experience diverse distribution changes. For Epimedium brevicornum Maxim, the phenomenon is obvious, but the understanding of the spatial dynamics of E. brevicornum under distinct time scales is poor. In this study, we modeled the potential distribution for E. brevicornum for five time scales, 1970–1979, 1980–1989, 1990–1999, 2000–2009, and 2010–2019, with different occurrence data, and the Kuenm package was used to optimize the parameter combination. Then, SDM tools and a Venn diagram were utilized to simulate the changes in highly suitable areas and spatial dynamics, respectively. Comprehensive results show that temperature seasonality (BIO4, 37.54%) has the greatest effect on the distribution of E. brevicornum, followed by minimum temperature (TMIN, 21.42%). The areas of distribution for E. brevicornum are 35.06 × 105 km2, 25.7 × 105 km2, 67.64 × 105 km2, 27.29 × 105 km2, and 9.87× 105 km2, which are mainly concentrated in Gansu, Shaanxi, Shanxi, and Henan, respectively. In addition, the largest regions for expansion, stability, and contraction under various time scales are 5.6 × 105 km2, 3.54 × 105 km2, and 3.47 × 105 km2, respectively. These changes indicate that approximately 7.96% of the regions are highly stable, and three critical counties, Wanyuan, Chenggu, and Hechuan, and Xixiang, have become significant areas for migration. Overall, our results indicate that there are different spatial distribution patterns and dynamics for E. brevicornum for different time scales. Given these results, this study also proposes comprehensive strategies for the conservation and management of E. brevicornum, which will further improve the current resource utilization status

Classification of Driver Distraction Risk Levels: Based on Driver’s Gaze and Secondary Driving Tasks

Driver distraction is one of the significant causes of traffic accidents. To improve the accuracy of accident occurrence prediction under driver distraction and to provide graded warnings, it is necessary to classify the level of driver distraction. Based on naturalistic driving study data, distraction risk levels are classified using the driver’s gaze and secondary driving tasks in this paper. The classification results are then combined with road environment factors for accident occurrence prediction. Two ways are suggested to classify driver distraction risk levels in this study: one is to divide it into three levels based on the driver’s gaze and the AttenD algorithm, and the other is to divide it into six levels based on secondary driving tasks and odds ratio. Random Forest, AdaBoost, and XGBoost are used to predict accident occurrence by combining the classification results, driver characteristics, and road environment factors. The results show that the classification of distraction risk levels helps improve the model prediction accuracy. The classification based on the driver’s gaze is better than that based on secondary driving tasks. The classification method can be applied to accident risk prediction and further driving risk warning

Growth behavior and kinetics of austenite grain in low-carbon high-strength steel with copper

A low-carbon high-strength steel with copper has better antibiological corrosion property, more widely used in large marine projects and ships. In this study, an austenite grain growth model of a low-carbon ship plate steel with 1.6Cu was established by using Sellars equation at 900 °C–1200 °C and different holding times (30–120 min) to reveal its kinetics. The pinning effect of grain boundary precipitates was studied by scanning electron microscopy (SEM) and transmission electron microscopy (TEM), and a quantitative relationship between the solid solution and precipitation behavior of copper bearing precipitates in experimental steel and austenite grain growth was analyzed. The experimental results show that the austenite grains grow slowly, and the grains are fine grains when the heating temperature is below 1000 °C and the transition temperature of rapid grain coarsening is 1000 °C. The relative error of dynamic model can be controlled within 8.5%. During heat treatment, Cu atoms are segregated at the grain boundary to form a copper-rich region, providing a coating effect on the carbide and grain boundary and hindering the growth of grains. With the increase in temperature, the diffusion rate of copper atoms increases, and the precipitates containing copper are rapidly dissolved into austenite. Therefore, the pinning effect is weakened, and the austenite grains grow rapidly