The optimal location and size of charging stations are important considerations in relation to the large-scale application of electric vehicles (EVs). In this context, considering that charging stations are both traffic service facilities and common electric facilities, a multi-objective model is built, with the objectives of maximizing the captured traffic flow in traffic networks and minimizing the power loss in distribution networks. There are two kinds of charging stations that are considered in this paper, and the planning of EV charge stations and distribution networks is jointly modelled. The formulated multi-objective optimization problem is handled by a fuzzy membership function. The genetic algorithm (GA) is used to solve the objective function. In case studies, a 33-node distribution system and a 25-node traffic network are used to verify the effectiveness of the proposed model. The location and capacity of two kinds of charging stations are designed in the case studies, after which the impact of the battery on the captured traffic flow is analyzed as well.

Human activity recognition (HAR) based on sensor data is a significant problem in pervasive computing. In recent years, deep learning has become the dominating approach in this field, due to its high accuracy. However, it is difficult to make accurate identification for the activities of one individual using a model trained on data from other users. The decline on the accuracy of recognition restricts activity recognition in practice. At present, there is little research on the transferring of deep learning model in this field. This is the first time as we known, an empirical study was carried out on deep transfer learning between users with unlabeled data of target. We compared several widely-used algorithms and found that Maximum Mean Discrepancy (MMD) method is most suitable for HAR. We studied the distribution of features generated from sensor data. We improved the existing method from the aspect of features distribution with center loss and get better results. The observations and insights in this study have deepened the understanding of transfer learning in the activity recognition field and provided guidance for further research.

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Bauhinia championi (Benth.) Benth. polysaccharides (BCBPs), extracted from Bauhinia championi (Benth.) Benth., which has been used in traditional Chinese medicine (TCM) for the treatment of osteoarthritis (OA), are the bioactive constituents of Bauhinia championi (Benth.) rattan. However, the molecular mechanisms responsible for their effects on OA are poorly understood. The Wnt/β-catenin signaling pathway plays an important role in the proliferation of chondrocytes. In the present study, the effects of BCBPs on Wnt/β-catenin signaling in chondrocytes were investigated. BCBPs were obtained by hot-water extraction and identified by the modified high performance liquid chromatography (HPLC) method. Chondrocytes were isolated from the knees of Sprague‑Dawley rats and identified by type II collagen immunohistochemistry. The chondrocytes were treated with or without BCBPs for 48 h. Cell viability was evaluated by MTT assay. The mRNA and protein levels of Wnt-4, β-catenin, Frizzled-2, glycogen synthase kinase (GSK)-3β, cyclin D1 and collagen II were detected by western blot analysis and reverse transcription PCR (RT-PCR), respectively. We found that the BCBPs contained at least seven monosaccharides, including D-mannose, rhamnose, D-(+) glucuronic acid, D-(+) galacturonic acid, D-glucose, galactose and arabinose. The cell viability of the chondrocytes treated with 50, 100 and 200 µg/ml BCBPs was significantly higher than that of the chondroctyes in the control group (treated with 0 µg/ml BCBPs). Furthermore, compared with the control group, the mRNA and protein expression of Wnt-4, β-catenin, Frizzled-2 and cyclin D1 in the BCBP-treated groups markedly increased, whereas the mRNA and protein expression of GSK-3β significantly decreased. Of note, the dose of 100 µg/ml BCBPs was more effective than the dose of 50 µg/ml BCBPs and 200 µg/ml BCBPs. In addition, we found that treatment with BCBPs upregulated the protein levels of collagen II in the chondrocytes. These results indicate that BCBPs upregulate Wnt/β-catenin signaling, thus promoting chondrocyte proliferation.