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Differentiated Instruction (DI) is a hot topic in educational research. Keeping abreast of its latest developments and frontiers can provide new perspectives for future study. Using CiteSpace softw...

As the number of African students in the international education market increases, it is important to understand their motivation to study in China and decision-making process they follow. This study focuses on African students being educated in Hangzhou, a new first-tier city. Using interview data, a tentative model on the push–pull factors affecting African students’ decision-making is presented. The findings show that African students’ decision-making process follows one of two sequences depending on whether they have received advice from others. All African students in China who were interviewed began to consider studying abroad due to personal reasons, recommendation from others, a lack of opportunity nearby, and the poor capacity of local universities along with social instability. For African students who do not have others’ advice to guide them, the subsequent stages of their decision-making process include choosing first to study in China and choosing a city and institution. This decision-making depends in large part on the information available online including program availability, reputation and rank of the university, its academic quality, the image of the city, and the availability of scholarships, the affordability of tuition and the cost of living, and application accessibility. By contrast, those who have access to others’ advice may skip the choice of host country and city, directly choosing the recommended institution.

Exosome and microRNAs (miRs) are implicated in ischemia/reperfusion (I/R) process. In this study, I/R mouse model was established, and exosomes derived from human umbilical cord mesenchymal stem cells (hUCMSCs) were isolated, identified, and injected to I/R mice to observe nerve injury and microglia M1 polarization. The differentially expressed genes in I/R microglia from databases were analyzed, and miRs differentially expressed in exosomes-treated microglia were analyzed by microarray. miR-26b-5p expression in hUCMSCs was intervened. Besides, microglia was extracted and co-cultured with SH-SY5Y or PC12 cells in oxygen-glucose deprivation/reperfusion (OGD/R) models to simulate I/R in vivo. Additionally, Toll-like receptor (TLR) activator GS-9620 was added to microglia. Exosomes alleviated nerve injury and inhibited M1 polarization in microglia. After I/R modeling, CH25H expression in microglia was upregulated but decreased after exosome treatment. miR-26b-5p was upregulated in microglia after exosome treatment and could target CH25H. Reduction in exosomal miR-26b-5p reversed the effects of hUCMSCs-exos on microglia. TLR pathway was activated in microglia after I/R but exosomes prevented its activation. Exosomal miR-26b-5p could repress M1 polarization of microglia by targeting CH25H to inactivate the TLR pathway, so as to relieve nerve injury after cerebral I/R. This investigation may offer new approaches for I/R treatment.

Microgrid consisting of distributed diesel generators, battery packs and distributed photovoltaics can provide effective power supply for residents in remote areas such as islands. However, due to fluctuations in load power consumption and distributed PV output, it needs be effective. The operational control method adjusts the power distribution to achieve cost-effective operation of the system and reliable power supply. Therefore, this paper proposes a microgrid optimal operation control strategy based on two-stage model prediction method. The first two-stage builds an optimal control problem based on an effective prediction of the power of each component to achieve optimal distribution of electrical energy. In order to improve the robustness of the control strategy to the prediction error, the second two-stage further adjusts the power generation of the diesel generator by solving the boundary value problem. The case study shows the effectiveness of the proposed control strategy in terms of computational feasibility, accuracy, robustness and cost reduction.

With the development of active distribution network, demand response, as an important adjustable resource, is introduced into the distribution network system to ensure the safe, stable and economic operation of the distribution network system under the combined action of distributed generation, energy storage and other equipment. However, the uncertainty of the external environment in the response process and the uncertainty of the price demand curve make the demand response have greater uncertainty in the current active distribution network system. Based on this, considering the reliable and economical operation of active distribution network, a scheduling optimization model of active distribution network considering demand response uncertainty is proposed in this paper, aiming to minimize the operating cost. This paper focuses on the analysis of two different types of demand response: incentive-based demand response and price-sensitive demand response, whose influence of uncertainty on costs is also considered. And the model is linearized by piecewise linearization. Finally, a modified IEEE33 node example is used to verify that the proposed model can improve the operation superiority of the system to a certain extent.

BACKGROUND: LncRNAs play key roles in glioma development, however, lncRNA F11-AS1’s effects has been unclearly in glioma.OBJECTIVE: F11-AS1 is an anti-tumor factor in glioma has been clearly until now.METHODS: Evaluating F11-AS1 expression by ISH in difference tissues and analysis the correlation with glioma prognosis in clinical. Using U87 and U251 cell to discuss lncRNA F11-AS1’s effect in glioma cancer cell biological activities by MTT, flow cytometry, transwell and wound healing assay. And measuring the relative miRNA and gene expressions by RT-qPCR and relative proteins expressions by WB assay. In next step, discuss the miR-3146 in F11-AS1 depressing cancer cell biological activities.RESULTS: The authors observed in this study that F11-AS1 was down-regulation in glioma and negatively correlated with miRNA-3146. Servival analysis showed that low level of F11-AS1 predicted poor survival. In glioma cells, F11-AS1 knockdown led to up-regulate, whereas F11-AS1 overexpression led to down-regulated miRNA-3146. Analysis of cell biological activities showed that F11-AS1 overexpression had effects to suppress glioma cell lines biological activities.CONCLUSION: Therefore, F11-AS1 down-regulates miRNA-3146 to depress cell biological activities in glioma.

Energy router (ER) is one of the core equipment for a micro-grid community. To coordinate the power flow among its terminals, centralized control is always applied. Centralized control relies on communications with a central controller and has lower reliability and flexibility. This work proposes a novel control strategy to achieve distributed power flow control without central controllers. The energy router has several terminals and each terminal is a three-phase Voltage Source Converter (VSC). All terminals only share a common DC link and have no other connections or information exchange. Each micro-grid is a self-governed entity and independently decides how much power is in need or can be provided. Every microgrid submits its power requirement to the ER in real-time together with an urgent coefficient and the ER decides how much to accept, fully or with a discount, according to the DClink voltage level. Simulations results are provided to validate the proposed solution for the operation of the energy router.

A large number of distributed energy access to the distribution network, which brings great risks to the safe and reliable operation of the power grid. According to the regulation characteristics of distributed generation, flexible load, reactive power regulating equipment and other adjustable resources in distribution network in terms of time scale and control function, combined with the requirements of operation economy and reliability of distribution network, the prediction error caused by the randomness and fluctuation of large-scale renewable energy output is considered. The multi-time scale multi-objective coordination optimization method is adopted to realize the active management of distribution network with high permeability distributed energy. In order to reduce the influence of renewable energy and load uncertainty on the operation of regional distribution network, the method optimizes the adjustable resources in distribution network from two stage of day-ahead and short-term, and realizes the safe, reliable and economic operation of distribution network with high permeability.