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Advancement of the oil tea industry requires the development of high-yielding and superior-quality varieties of Camellia oleifera, a major oilseed crop. However, traditional breeding methods, hampered by lengthy cycles and low selection accuracy, significantly constrain the breeding process. Identifying single nucleotide polymorphisms (SNPs) associated with target traits, and applying molecular marker-assisted selection (MAS) for these traits, can thereby shorten the breeding cycles and amplify the breeding efficiency. In this study, we utilized the hexaploid C. oleifera as the reference genome to identify high-quality SNPs and constructed a high-density genetic linkage map of C. oleifera that spanned 1566.733 cM, included 3097 SNPs, and was anchored to 15 linkage groups. Using interval mapping, we localized quantitative trait loci (QTLs) for 11 juvenile traits in C. oleifera, identifying 15 QTLs for growth traits and 24 QTLs for leaf traits, including 4 stable QTLs. The logarithm of odds (LOD) scores for individual QTLs ranged from 3.48 to 14.62, explaining 9.86–48.61% of the phenotypic variance. We further identified 2 SNPs associated with growth traits (marker11-951 and marker12-68) and 10 SNPs associated with leaf traits (marker11-276, marker11-410, marker11-560, marker13-16, marker13-39, marker13-110, marker13-731, marker14-701, marker14-910, and marker14-1331). These results provide valuable insights into the genetic mapping of key traits in C. oleifera and will contribute to the development of new varieties with high yield and superior quality in the future. [ABSTRACT FROM AUTHOR]

The electronic and nonlinear optical (NLO) properties of Al13–X and 2Al13–X (where X represents dianhydrides BPDA, BTDA, ODPA, and 6FDA) were systematically investigated using (time-dependent) density functional theory methods. It was found that Al13 could effectively bind to dianhydride molecules via two strong Al–O bonds with high binding energies. Compared to pristine Al13 and dianhydrides, hybridized complexes Al13–X exhibit significant enhancements in both linear and nonlinear optical response properties, as evidenced by the calculated isotropic polarizability and static/dynamic first hyperpolarizabilities, respectively. The nature of the large first hyperpolarizabilities of Al13–X complexes can be understood by analyzing the low excitation energies of the key excited states and the first hyperpolarizability density. Furthermore, the dianhydride ligand is capable of bridging two aluminum clusters to form a novel D–A–D molecule, which further enhances the NLO properties of the molecules. It is hoped that the current research work will provide ideas for the rational design of such inorganic–organic hybrid complexes as novel functional electro-optical materials. [ABSTRACT FROM AUTHOR]

The Yolov4 detection algorithm does not sufficiently extract local semantic and location information. This study aims to solve this problem by proposing a Yolov4-based multiscale feature fusion detection system for high-speed train wheel tread defects. First, multiscale feature maps are obtained from a feature extraction backbone network. The proposed multiscale feature fusion network then fuses the underlying features of the original three scales. These fused features contain more defect semantic information and location details. Based on the fused features, a path aggregation network is used to fuse feature maps at different resolutions, with an improved loss function that speeds up the convergence of the network. Experimental results show that the proposed method is effective at detecting defects in the wheel treads of high-speed trains., Author(s): Changfan Zhang [1]; Xinliang Hu [2]; Jing He (corresponding author) [1]; Na Hou [1] 1. Introduction High-speed train fault diagnosis is crucial for the safe operation and maintenance of [...]

Purposes To explore the teaching effect and value of virtual reality technology combined with PBL teaching method applied to sports anatomy.Procedures 119 undergraduate students majoring in physical education of Xianyang Normal University were selected as research objects.Randomly divided into experimental group (N=59) and control group (N=60).Methods The experimental group used virtual reality technology combined with PBL teaching method, and the control group used traditional teaching method to teach. At the end of the course, the test scores of the two groups and the evaluation results of self-learning effect were statistically analyzed. Results the test scores of the students in the experimental group were significantly higher than those in the control group (P

This article discusses the synthesis of ynamides, a class of N-alkynyl compounds, through various catalytic reactions. The authors highlight the importance of ynamides in the synthesis of nitrogen-containing scaffolds and summarize existing methods for their synthesis. They also present their own research on the direct catalytic addition of terminal alkynes to azodicarboxylates to produce ynehydrazides, which can then be converted into ynamides. The authors propose potential future directions for further research in this field. [Extracted from the article]

Countries with different democratic levels tend to show various degrees of emphasis on military expenditure and a consensus can hardly be reached on the economic effect of democracy and military expenditure. By applying a panel vector autoregressive (PVAR) approach, this article examines the potential dynamic and endogenous relationships among democracy, military expenditure and economic growth of 126 countries from 1990 to 2020. Furthermore, the k-means clustering algorithm is employed to account for the heterogeneous interaction between democracy and military expenditure in different countries. The empirical results reveal that the strong positive impact of democracy and the negative effect of military spending on economic growth exists in the full sample and the cluster of countries with low democratic levels and a high military burden. For democratic countries with low military expenditure, there is a more significant and negative impact both of military expenditure on democracy and vice versa. [ABSTRACT FROM AUTHOR]

With the advent of smart cities, the significance of the Internet of Things (IoT) is gaining greater prominence. At the same time, the safety early warning system in the IoT has a significant impact on real-time monitoring and the response to potential risks. Despite the advancements made in edge-assisted IoT deployments, several challenges and constraints persist. Given the potential threat to life posed by safety-related messages, ensuring the authenticity of messages in the edge-assisted IoT safety warning system is crucial. However, considering the identity privacy of devices participating in the edge-assisted Internet of Things system, directly verifying the identity of the sending device is undesirable. To address this issue, in this work, we design a linkable group signature scheme that allows devices to anonymously send safety-related messages to edge nodes, defending against Sybil attacks while ensuring the traceability of malicious device identities. Then, we present a high-efficiency conditional privacy-preserving authentication (CPPA) scheme based on the designed group signatures for the safety warning system in edge-assisted IoT. This scheme effectively protects device identity privacy while providing a reliable authentication mechanism to ensure the credibility and traceability of alert messages. The proposed scheme contributes to the field of safety warning systems in the context of edge-assisted IoT, providing a robust solution for privacy preservation and authentication. [ABSTRACT FROM AUTHOR]