Wu bei zhi /

Wood block print."Juan 240" shows Zheng He's voyager route from Nanjing, passing through South East Asia, Indian Ocean, Red Sea, all the way to Persian Gulf.Early Qing Dynasty ed., prefaced Tianqi 1 (1621).Juan (chapter) 240 is one of 80 volumes in 8 cases (30 x 19 cm.)."Wu bei zhi juan er bai si shi."The 80 vols. set is kept in Chinese Rare Book Cage. DLCOn double leaves, oriental style

Understanding the intention to donate online in the Chinese context: The influence of norms and trust

Due to the advancement of information and communication technologies, online donations have become unprecedentedly convenient, making money received from individual online donations an important form of revenue for many charitable organizations in China. However, factors contributing to people’s online donation intentions, in turn impacting donating behavior, have been under-examined. The current study aims to understand factors influencing online donation intention in the Chinese cultural context by combining constructs from the extended Theory of Planned Behavior (TPB; including the original TPB constructs and moral norm) and trust-related constructs (i.e., trust in charity organizations and trust in technology). The moderation effect of past donation behavior on the relationship between trust and donation intention was also explored. A total of 721 Chinese participants completed the online survey. SPSS was used to perform hierarchical multiple regressions. The results showed that attitude, perceived behavioral control, moral norm, and subjective norm were all positively related to online donation intention. Moral norm was found to be a stronger predictor than subjective norm, raising the amount of explained variance of the original TPB model. Trust in charity organizations was found to positively predict donation intention while trust in technology was not. The results also revealed that past donation behavior moderated the effect of trust in charity organizations on donation intention. This study not only adds to the body of knowledge on charitable donation in the online context by incorporating two trust-related constructs into the extended TPB model, but also highlights the different roles moral and subjective norms play in predicting people’s prosocial behavior in the context of Chinese culture

Application of Computer-aided Diagnosis System Based on Deep Learning in Rib Fracture Diagnosis

Objective: To investigate the application value of computer-aided diagnosis (CAD) system based on deep learning (DL) in rib fracture diagnosis. Methods: The CT images of 232 patients with chest trauma were analyzed retrospectively and the films were read in three ways. CAD system reading: using CAD system to detect and record the results of rib fracture; radiologists reading: two radiologists with 6 years of CT diagnosis experience read the film independently and the diagnostic results were based on the consensus of them; radiologists reading with the assistance of CAD system: one month later, the same two radiologists reassessed the images with the aid of the CAD system using a joint reading mode. Gold standard: two senior radiologists with more than 15 years of experience in the CT diagnosis of rib fractures read the radiographs independently and the consensus of them was used as the diagnostic standard. The sensitivity, false-positive rate and the reading time of the three methods were calculated and compared. Results: A total of 712 rib fractures were found in 232 patients. The reading sensitivity of the CAD system was 81.2%, which was lower than that of the radiologists, and the reading sensitivity of the radiologists was lower than that of CAD system-assisted radiologists. The false positive rate of CAD system was 0.48±0.13 and was the highest . There was no statistical difference in the false-positive rate between radiologists and CAD system-assisted radiologists. The reading time of the CAD system was (2.45±0.92)s and was the shortest. The reading time of CAD system-assisted radiologists was less than that of radiologists and the reading time was reduced by 34.2%. Conclusion: To further improve the sensitivity and reduce the false positive rate is an important part of CAD improvement; the use of CAD system based on deep learning to assist radiologists in reading images can improve the sensitivity of rib fracture diagnosis and reduce the time of reading images without increasing the false positive rate

Research on Physiological Characteristics and Differential Gene Expression of Rice Hybrids and Their Parents under Salt Stress at Seedling Stage

Soil salinization is one of the most important abiotic stresses which can seriously affect the growth and development of rice, leading to the decrease in or even loss of a rice harvest. Increasing the rice yield of saline soil is a key issue for agricultural production. The utilization of heterosis could significantly increase crop biomass and yield, which might be an effective way to meet the demand for rice cultivation in saline soil. In this study, to elucidate the regulatory mechanisms of rice hybrids and their parents that respond to salt stress, we investigated the phenotypic characteristics, physiological and biochemical indexes, and expression level of salt-related genes at the seedling stage. In this study, two sets of materials, encapsulating the most significant differences between the rice hybrids and their parents, were screened using the salt damage index and a hybrid superiority analysis. Compared with their parents, the rice hybrids Guang-Ba-You-Hua-Zhan (BB1) and Y-Liang-You-900 (GD1) exhibited much better salt tolerance, including an increased fresh weight and higher survival rate, a better scavenging ability towards reactive oxygen species (ROS), better ionic homeostasis with lower content of Na+ in their Na+/K+ ratio, and a higher expression of salt-stress-responsive genes. These results indicated that rice hybrids developed complex regulatory mechanisms involving multiple pathways and genes to adapt to salt stress and provided a physiological basis for the utilization of heterosis for improving the yield of rice under salt stress

Metabolite Profiling and Transcriptome Analysis Provide Insight into Seed Coat Color in Brassica juncea

The allotetraploid species Brassica juncea (mustard) is grown worldwide as oilseed and vegetable crops; the yellow seed-color trait is particularly important for oilseed crops. Here, to examine the factors affecting seed coat color, we performed a metabolic and transcriptomic analysis of yellow- and dark-seeded B. juncea seeds. In this study, we identified 236 compounds, including 31 phenolic acids, 47 flavonoids, 17 glucosinolates, 38 lipids, 69 other hydroxycinnamic acid compounds, and 34 novel unknown compounds. Of these, 36 compounds (especially epicatechin and its derivatives) accumulated significantly different levels during the development of yellow- and dark-seeded B. juncea. In addition, the transcript levels of BjuDFR, BjuANS,BjuBAN, BjuTT8, and BjuTT19 were closely associated with changes to epicatechin and its derivatives during seed development, implicating this pathway in the seed coat color determinant in B. juncea. Furthermore, we found numerous variations of sequences in the TT8A genes that may be associated with the stability of seed coat color in B. rapa, B. napus, and B. juncea, which might have undergone functional differentiation during polyploidization in the Brassica species. The results provide valuable information for understanding the accumulation of metabolites in the seed coat color of B. juncea and lay a foundation for exploring the underlying mechanism

Additional file 1 of Promoting collateral formation in type 2 diabetes mellitus using ultra-small nanodots with autophagy activation and ROS scavenging

Supplementary Material