New hanger design approach of tied-arch bridge to enhance its robustness

As the crucial components among the tied-arch bridge, the local failure of hangers may trigger a progressive collapse through the entire tied-arch bridge. However, the current design guidance as regards hangers still lacks consideration of structure robustness under an extreme hazard. To improve the structural robustness of tied-arch bridge under extreme conditions, a new hanger design method is proposed, which is termed as asymmetric parallel double-hanger system. Based on Miner’s linear cumulative damage law, an analysis on the fatigue life of the double-hanger system was conducted to verify the feasibility of the proposal, and then a dynamic time-history analysis was employed to simulate the transitory fracture impact due to one or more hangers fracturing. According to the simulation results, the structural robustness is greatly enhanced with asymmetric parallel-double hanger system design, when compared with single hanger system design. When one or more hangers reveal local damage, it will not trigger a progress failure to the whole structure in particular. Several practical suggestions of bridge system’s load-carrying capacity are also put forward for the future arch bridge design at the end of this paper. © 2018 Korean Society of Civil Engineer

Bacterial community assembly driven by temporal succession rather than spatial heterogeneity in Lake Bosten: a large lake suffering from eutrophication and salinization

Oligosaline lakes in arid and semi-arid regions play a crucial role in providing essential water resources for local populations. However, limited research exists on the impact of the environment on bacterial community structure in these lakes, co-occurrence patterns and the mechanisms governing bacterial community assembly. This study aims to address this knowledge gap by examining samples collected from five areas of Lake Bosten over four seasons. Using the 16S rRNA gene sequencing method, we identified a total of 510 to 1,005 operational taxonomic units (OTUs) belonging to 37 phyla and 359 genera in Lake Bosten. The major bacterial phyla were Proteobacteria (46.5%), Actinobacteria (25.9%), Bacteroidetes (13.2%), and Cyanobacteria (5.7%), while the major genera were hgcI_clade (12.9%), Limnohabitans (6.2%), and Polynucleobacter (4.7%). Water temperature emerged as the primary driver of these community structure variations on global level. However, when considering only seasonal variations, pH and nitrate were identified as key factors influencing bacterial community structures. Summer differed from other seasons in aspects of seasonal symbiotic patterns of bacterial communities, community assembly and function are different from other seasons. There were notable variations in bacterial community structures between winter and summer. Deterministic processes dominated community assembly, but there was an increase in the proportion of stochastic processes during summer. In summer, the functions related to photosynthesis, nitrogen fixation, and decomposition of organic matter showed higher abundance. Our findings shed light on the response of bacterial communities to environmental changes and the underlying mechanisms of community assembly in oligosaline lakes in arid regions

Two B-Box Proteins, MaBBX20 and MaBBX51, Coordinate Light-Induced Anthocyanin Biosynthesis in Grape Hyacinth

Floral colour is an important agronomic trait that influences the commercial value of ornamental plants. Anthocyanins are a class of flavonoids and confer diverse colours, and elucidating the molecular mechanisms that regulate their pigmentation could facilitate artificial manipulation of flower colour in ornamental plants. Here, we investigated the regulatory mechanism of light-induced anthocyanin biosynthesis during flower colouration in grape hyacinth (Muscari spp.). We studied the function of two B-box proteins, MaBBX20 and MaBBX51. The qPCR revealed that MaBBX20 and MaBBX51 were associated with light-induced anthocyanin biosynthesis. Both MaBBX20 and MaBBX51 are transcript factors and are specifically localised in the nucleus. Besides, overexpression of MaBBX20 in tobacco slightly increased the anthocyanin content of the petals, but reduced in MaBBX51 overexpression lines. The yeast one-hybrid assays indicated that MaBBX20 and MaBBX51 did not directly bind to the MaMybA or MaDFR promoters, but MaHY5 did. The BiFC assay revealed that MaBBX20 and MaBBX51 physically interact with MaHY5. A dual luciferase assay further confirmed that the MaBBX20–MaHY5 complex can strongly activate the MaMybA and MaDFR transcription in tobacco. Moreover, MaBBX51 hampered MaBBX20–MaHY5 complex formation and repressed MaMybA and MaDFR transcription by physically interacting with MaHY5 and MaBBX20. Overall, the results suggest that MaBBX20 positively regulates light-induced anthocyanin biosynthesis in grape hyacinth, whereas MaBBX51 is a negative regulator

Mn3O4/Co(OH)(2) cactus-type nanoarrays for high-energy-density asymmetric supercapacitors

Mn3O4/Co(OH)(2) cactus-type nanoarrays for high-energy-density asymmetric supercapacitor

A novel brain inception neural network model using EEG graphic structure for emotion recognition

Purpose EEG analysis of emotions is greatly significant for the diagnosis of psychological diseases and brain-computer interface (BCI) applications. However, the applications of EEG brain neural network for emotion classification are rarely reported and the accuracy of emotion recognition for cross-subject tasks remains a challenge. Thus, this paper proposes to design a domain invariant model for EEG-network based emotion identification. Methods A novel brain-inception-network based deep learning model is proposed to extract discriminative graph features from EEG brain networks. To verify its efficiency, we compared our proposed method with some commonly used methods and three types of brain networks. In addition, we also compared the performance difference between the EEG brain network and EEG energy distribution for emotion recognition. Result One public EEG-based emotion dataset (SEED) was utilized in this paper, and the classification accuracy of leave-one-subject-out cross-validation was adopted as the comparison index. The classification results show that the performance of the proposed method is superior to those of the other methods mentioned in this paper. Conclusion The proposed method can capture discriminative structural features from the EEG network, which improves the emotion classification performance of brain neural networks

Development of a New Manufacturing Route for Benzoylphenylureas and Their Key Intermediates

A new and efficient manufacturing technology is disclosed in the present work for the preparation of benzoylphenylureas and their key intermediates. This new route significantly reduces the number of reaction steps from six to three, resulting in a streamlined process. Additionally, the overall yield is increased from 56% to over 69%. Compared to the original process route, the new manufacturing route has the advantages of fewer chemical steps, higher overall yield, less process safety hazard and environmental impact. Considering these factors, the new manufacturing route exhibits considerable potential for industrialization.</p