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At present, the optimization of public transportation networks and vehicle scheduling are carried out independently in stages. However, through analysis, it has been found that scheduling information such as route schedules is an important factor related to passenger route selection. Therefore, in order to further improve the optimization effect, this article proposes an innovative idea of simultaneously optimizing the line network and scheduling. Based on the construction of a real–virtual public transportation network, this article constructs a synchronous optimization model for the line network and scheduling by considering both passenger waiting and on-board time. To achieve the consideration of passengers for different route choices, a shortest path traversal algorithm based on Yen was proposed to analyze the number and weight of the shortest paths between the same OD, and a genetic algorithm was used to solve the model. Finally, the effectiveness of the model was verified through numerical examples, and the results showed that synchronous optimization was superior to phased optimization: the passenger time cost was reduced by 21.5%, the bus operation cost was reduced by 13.7%, and the total bus system cost was reduced by 18.0%.

The public’s support for emergency infrastructure projects, which will affect the government’s credibility, social stability, and development, is very important. However, there are few systematic research findings on public support for emergency infrastructure projects. In order to explore the factors influencing the public’s support and the degree of influence of each factor on the public’s support, this paper employs K-Nearest Neighbors (KNN), a learning curve with m-fold cross-validation, grid search, and random forest to study the public’s support for emergency infrastructure projects and its influencing factors. In this paper, a prediction model of the public’s support for emergency infrastructure projects is developed based on KNN from data drawn from a questionnaire survey of 445 local residents concerning Wuhan Leishenshan Hospital, China. Two optimization algorithms, the learning curve with m-fold cross-validation and the grid search algorithm, are proposed to optimize the key parameters of the KNN predictive model. Additionally, quantitative analysis is conducted by using the random forest algorithm to assess the importance of various factors influencing public support. The results show that the prediction accuracy and model stability of the KNN prediction model based on the grid search algorithm are better than those using a learning curve with m-fold cross-validation. Furthermore, the random forest algorithm quantitative analysis shows that the most important factor influencing the public’s support is government attention. The conclusions drawn from this paper provide a theoretical reference and practical guidance for decision making and the sustainable development of emergency infrastructure projects in China.

The research on the high-value utilization of biomass has good application prospects and is conducive to sustainable development. In this paper, three different types of activators (potassium hydroxide, phosphoric acid, and polypropylene) were used to carbonize jujube branches at high temperatures of 600 °C and 800 °C, and then the PEG/jujube charcoal composite phase change materials (PCM) were prepared by vacuum impregnation of polyethylene glycol (PEG). The results showed that the carbon support activated by polypropylene (PP) had a richer pore size distribution than the other two activation methods, and the 800 °C carbonization carrier loaded PEG had a higher phase change enthalpy than the composite material at 600 °C. The mesoporous and macroporous structures were staggered with PP-activated jujube charcoal at 800 °C, with a specific surface area of 1082.2 m²/g, the melting enthalpy of the composite material reached 114.92 J/g, and the enthalpy of solidification reached 106.15 J/g after PEG loading. The diffraction peak of the composite phase change material was the superposition of PEG and carbon matrix, which proved that the loading process was physical adsorption. After 200 thermal cycles, the melting enthalpy and crystallization enthalpy were only reduced by 4.3% and 4.1%, respectively, and they remained stable and leak-free at the melting point of PEG for 2 h, demonstrating good thermal stability of the composite phase change materials. In summary, PP has obvious advantages over traditional activation, and the carbon-supported PEG phase change composite after PP activation is a biochar energy storage material with excellent performance.

Cardiovascular stents enable the rapid re-endothelialization of endothelial cells (ECs), and the constant suppression of smooth muscle cell (SMC) proliferation has been proved to effectively prevent thrombosis. However, the development and application of such stents are still insufficient due the delayed re-endothelialization progress, as well as the poor durability of the SMC inhibition. In this paper, we developed a mussel-inspired coating with the ability for the dual delivery of both growth factor (e.g., platelet-derived growth factor, PDGF) and therapeutic gas (e.g., nitric oxide, NO) for thrombosis prevention. We firstly synthesized the mussel-inspired co-polymer (DMHM) of dopamine methacrylamide (DMA) and hydroxyethyl methacrylate (HEMA) and then coated the DMHM on 316L SS stents combined with CuII. Afterwards, we immobilized the PDGF on the DMHM-coated stent and found that the PDGF could be released in the first 3 days to enhance the recruitment, proliferation, and migration of human umbilical vein endothelial cells (HUVECs) to promote re-endothelialization. The CuII could be “sealed” in the DMHM coating, with extended durability (2 months), with the capacity for catalyzed NO generation for up to 2 months to suppress the proliferation of SMCs. Such a stent surface modification strategy could enhance the development of the cardiovascular stents for thrombosis prevention.

Research has proven that counselling services are essential to solving the troubles in the mental health of international Chinese students in the post-epidemic stage. Online questionnaires were implemented for about 1000 international Chinese college students from three universities in Thailand. Results showed that female junior and senior students who stayed in post-pandemic Thailand longer than others were likely to suffer from mental health disorders. In addition, in Thailand, counselling has a significant positive association with the mental health status of the students. Therefore, it is recommended in this study that Thai universities should provide more counselling services to support students in focusing on education and adjusting or adapting to the environment abroad.

Flexible interconnection transformation of a distribution network using all-control power electronics technology will help to overcome the technical bottleneck of distributed generation (DG) penetration and high-quality power supply in the traditional distribution network. However, the flexible interconnection form that uses back-to-back power electronic converters to replace tie switches has disadvantages such as high cost and large footprint, so its mass promotion and application are bound to be limited. Therefore, a new topology of flexible interconnected distribution network with embedded DC system (FDN+EDC) with a better economy is proposed. Firstly, the topology of FDN+EDC is introduced to improve the controllability level of the distribution network under high percentage DG penetration, and is compared with the conventional flexible interconnection method. Secondly, in order to realize the coordinated optimal economic operation of source, network and load in the FDN+EDC, a dynamic reconfiguration model of switches status and continuous adjustment of flexible interconnection device (FID) are proposed. Then, to achieve a fast and globally optimal solution of the model, a hierarchical coordinated optimization strategy is designed based on an improved particle swarm algorithm for the optimization of discrete and continuous variables. Finally, the validity of the algorithm is verified, and an 88-node FDN+EDC is constructed to verify the advantages of the proposed embedded DC flexible interconnection topology and realize the joint optimal dispatch of network-source-load.

The anthocyanin biosynthesis attracts strong interest due to the potential antioxidant value and as an important morphological marker. However, the underlying mechanism of anthocyanin accumulation in plant tissues is not clearly understood. Here, a rice mutant with a purple color in the leaf blade, named pl6, was developed from wild type (WT), Zhenong 41, with gamma ray treatment. By map-based cloning, the OsPL6 gene was located on the short arm of chromosome 6. The multiple mutations, such as single nucleotide polymorphism (SNP) at −702, −598, −450, an insertion at −119 in the promoter, three SNPs and one 6-bp deletion in the 5′-UTR region, were identified, which could upregulate the expression of OsPL6 to accumulate anthocyanin. Subsequently, the transcript level of structural genes in the anthocyanin biosynthesis pathway, including OsCHS, OsPAL, OsF3H and OsF3′H, was elevated significantly. Histological analysis revealed that the light attenuation feature of anthocyanin has degraded the grana and stroma thylakoids, which resulted in poor photosynthetic efficiency of purple leaves. Despite this, the photoabatement and antioxidative activity of anthocyanin have better equipped the pl6 mutant to minimize the oxidative damage. Moreover, the contents of abscisic acid (ABA) and cytokanin (CK) were elevated along with anthocyanin accumulation in the pl6 mutant. In conclusion, our results demonstrate that activation of OsPL6 could be responsible for the purple coloration in leaves by accumulating excessive anthocyanin and further reveal that anthocyanin acts as a strong antioxidant to scavenge reactive oxygen species (ROS) and thus play an important role in tissue maintenance.

OsmiR535 belongs to the miR156/miR529/miR535 superfamily, a highly conserved miRNA family in plants. OsmiR535 is involved in regulating the cold-stress response, modulating plant development, and determining panicle architecture and grain length. However, the role that OsmiR535 plays in plant responses to drought and salinity are elusive. In the current study, molecular and genetic engineering techniques were used to elucidate the possible role of OsmiR535 in response to NaCl, PEG(Poly ethylene glycol), ABA(Abscisic acid), and dehydration stresses. Our results showed that OsmiR535 is induced under stressed conditions as compared to control. With transgenic and CRISPR/Cas9 knockout system techniques, our results verified that either inhibition or knockout of OsmiR535 in rice could enhance the tolerance of plants to NaCl, ABA, dehydration and PEG stresses. In addition, the overexpression of OsmiR535 significantly reduced the survival rate of rice seedlings during PEG and dehydration post-stress recovery. Our results demonstrated that OsmiR535 negatively regulates the stress response in rice. Moreover, our practical application of CRISPR/Cas9 mediated genome editing created a homozygous 5 bp deletion in the coding sequence of OsmiR535, demonstrating that OsmiR535 could be a useful genetic editing target for drought and salinity tolerance and a new marker for molecular breeding of Oryza sativa.