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To solve the mismatch between the supply and demand of shared electric vehicles (SEVs) caused by the uneven distribution of SEVs in space and time, an SEV relocating optimization model is designed based on a reward mechanism. The aim of the model is to achieve a cost-minimized rebalancing of the SEV system. Users are guided to attend the relocating SEVs by a reward mechanism, and employees can continuously relocate multiple SEVs before returning to the supply site. The optimization problem is solved by a heuristic column generation algorithm, in which the driving routes of employees are added into a pool by column generation iteratively. In the pricing subproblem of column generation, the Shuffled Complex Evolution–University of Arizona (SCE–UA) is designed to generate a driving route. The proposed model is verified with the actual data of the Dalian city. The results show that our model can reduce the total cost of relocating and improve the service efficiency.

Fibroblast growth factor 21 (FGF21) is secreted by hepatocytes as a peptide hormone to regulate glucose and lipid metabolism. FGF21 promotes hepatic ketogenesis and increases ketone body utilization in starvation. Histones are the target molecules of nutrients in regulating hepatic metabolic homeostasis. However, the effect of ketone bodies on FGF21 expression and the involvement of histones in it is not clear yet. The present study observed the effects of β-hydroxybutyrate (β-OHB), the main physiological ketone body, on FGF21 expression in human hepatoma HepG2 cells in vitro and in mice in vivo, and the role of histone deacetylases (HDACs) in β-OHB-regulated FGF21 expression was investigated. The results showed that β-OHB significantly upregulated FGF21 gene expression and increased FGF21 protein levels while it inhibited HDACs’ activity in HepG2 cells. HDACs’ inhibition by entinostat upregulated FGF21 expression and eliminated β-OHB-stimulated FGF21 expression in HepG2 cells. Intraperitoneal injections of β-OHB in mice resulted in the elevation of serum β-OHB and the inhibition of hepatic HDACs’ activity. Meanwhile, hepatic FGF21 expression and serum FGF21 levels were significantly increased in β-OHB-treated mice compared with the control. It is suggested that β-OHB upregulates FGF21 expression through inhibition of HDACs’ activity in hepatocytes.

PurposeSodium-glucose cotransporter 2 (SGLT2) inhibitors have cardiorenal protective effects regardless of whether they are combined with type 2 diabetes mellitus, but their specific pharmacological mechanisms remain undetermined.Materials and MethodsWe used databases to obtain information on the disease targets of “Chronic Kidney Disease,” “Heart Failure,” and “Type 2 Diabetes Mellitus” as well as the targets of SGLT2 inhibitors. After screening the common targets, we used Cytoscape 3.8.2 software to construct SGLT2 inhibitors' regulatory network and protein-protein interaction network. The clusterProfiler R package was used to perform gene ontology functional analysis and Kyoto encyclopedia of genes and genomes pathway enrichment analyses on the target genes. Molecular docking was utilized to verify the relationship between SGLT2 inhibitors and core targets.ResultsSeven different SGLT2 inhibitors were found to have cardiorenal protective effects on 146 targets. The main mechanisms of action may be associated with lipid and atherosclerosis, MAPK signaling pathway, Rap1 signaling pathway, endocrine resistance, fluid shear stress, atherosclerosis, TNF signaling pathway, relaxin signaling pathway, neurotrophin signaling pathway, and AGEs-RAGE signaling pathway in diabetic complications were related. Docking of SGLT2 inhibitors with key targets such as GAPDH, MAPK3, MMP9, MAPK1, and NRAS revealed that these compounds bind to proteins spontaneously.ConclusionBased on pharmacological networks, this study elucidates the potential mechanisms of action of SGLT2 inhibitors from a systemic and holistic perspective. These key targets and pathways will provide new ideas for future studies on the pharmacological mechanisms of cardiorenal protection by SGLT2 inhibitors.

In narrow water channels, ship traffic may be affected by water flows and ship interactions. Studying their effects can help maritime authorities to establish appropriate management strategies. In this study, a two-lane cellular automation model is proposed. Further, the behavior of ship traffic is analyzed by setting different water flow velocities and considering ship interactions. Numerical experiment results show that the ship traffic density-flux relation is significantly different from the results obtained by classical models. Furthermore, due to ship interactions, the ship lane-change rate is influenced by the water flow to a certain degree.

Abstract Quantum dot-sensitized solar cells based on fluorine-doped tin oxide (FTO)/Au/TiO2/CdS photoanode and polysulfide electrolyte are fabricated. Au nanoparticles (NPs) as interfacial layer between FTO and TiO2 layer are dip-coated on FTO surface. The structure, morphology and impedance of the photoanodes and the photovoltaic performance of the cells are investigated. A power conversion efficiency of 1.62% has been obtained for FTO/Au/TiO2/CdS cell, which is about 88% higher than that for FTO/TiO2/CdS cell (0.86%). The easier transport of excited electron and the suppression of charge recombination in the photoanode due to the introduction of Au NP layer should be responsible for the performance enhancement of the cell.

Collaborative problem-solving (CPS) learning is increasingly valued for its role in promoting higher-order thinking of learners. Despite the widespread application of role scripts in CPS, little is known about the mechanisms by which roles influence learners' cognition and the impact of goal orientation on roles. In this study, we designed role scripts and goal-orientation scripts to facilitate CPS. Then, a total of 32 postgraduate students participated in CPS and they were divided into 8 groups, among which two roles of analyst and commenter were assigned respectively. Through qualitative and quantitative analysis, this study explored the differences between the two roles in terms of discourse space rotation, types of cognitive activities and epistemic network structure, and the function played by goal orientation. Results showed that there was a general structure in CPS, that analysts and commenters have different functional biases, and that goal orientation influences the function of the roles. This study clarified the cognitive contribution of different roles, and the respective strength of different goal orientation. The findings may provide instructors with implications for designing scripts and organizing CPS in the classroom context.

Artificial Intelligence (AI) has become an important technology affecting the development of society and education, and it is crucial to explore AI to enhance students' creativity and learning performance. This research proposes the model and hypothesis based on the resource-based theory and related research. AI of higher education institute (HEI) affects students' learning performance and combines the existing literature to develop measurement tools and to obtain a formal questionnaire after pre-research and received 561 valid questionnaires collected from HEIs in China that have applied AI. Then we used SmartPLS 3.0 to construct a partial least squares structural equation model (PLS-SEM) for data analysis on the received data samples. The research results show that: (1) HEIs' artificial intelligence capability is a three-order variable and formed by three formative second-order variables such as resources (data, technical, basic resources), skills (technical skills, teaching applications, collaboration competencies), and consciousness (reform, innovation consciousness); (2) HEIs' artificial intelligence capability significantly affects students' self-efficacy and creativity; (3) HEIs' artificial intelligence capability affects students' learning performance via two mediating variables: student creativity and self-efficacy. This study focuses on AI applications within the HEI, confirms the new explanatory power of resource-based theory in technological practices, and deconstructs the intrinsic mechanics, especially in relationships between students' creativity, self-efficacy, and learning performance. This research also puts forward suggestions to reserve and deploy artificial intelligence resources, improve the digital literacy of teachers and students, use AI to drive teaching and learning, and improve students' creativity and learning performance.