Low-carbon Economy and Research on the Strategy Transformation of China’s Small and Medium Enterprises

At present, low-carbon economy has become the great trend in the development of global economy under the serious climate environment gradually. China’s small and medium enterprises (SME) have taken the large proportions in national economy, which face large amount of opportunities and challenges in the wave of reform. This article analyses the current situation and the problems on development strategy, technology innovation and the path of reform of China’s SME, which takes examples by the SME in some regions to improve the operating environments. It expects to change the extensive production mode, strengthen the management capability and technology innovation in China’s SME. Under the basis of this research, the article concludes the relevant strategy transformation modes, which provides the references and evidences for China’s SME

Capecitabine treatment of HCT-15 colon cancer cells induces apoptosis via mitochondrial pathway

Purpose: To investigate the effect of capecitabine on apoptosis induction in HCT-15 colon carcinoma cells and investigate the underlying mechanism.Methods: Phase-contrast microscopy was used for the examination of morphological changes while flow cytometry was employed for the analysis of cell cycle distribution, induction of apoptosis, reactive oxygen species (ROS) production and expression of caspases. Western blot assay was used for the analysis of expression level of apoptosis-related and cell cycle regulatory proteins.Results: Capecitabine treatment caused changes in the morphological appearance of HCT-15 cells after 48 h. The viability of HCT-15 cells was reduced to 23 % on treatment with capecitabine (5 μM) compared to 98 % in the control cultures. Incubation with capecitabine increased the population of HCT- 15 cells in G0/G1 phase to 56.43 % compared to 41.67 % in the control. Capecitabine treatment of HCT-15 cells caused condensation of DNA and induced apoptosis in a concentration-dependent manner. At 5 μM concentration of capecitabine, apoptosis was induced in 45.74 % of the cells. Incubation of HCT-15 cells with capecitabine for 48 h led to a significant increase in the production of ROS. Translocation of Endo G and AIF from mitochondria to the nuclei increased significantly (p < 0.005) on treatment with 5 μM capecitabine. Capecitabine treatment also reduced the expression of cyclin E and Cdc25c and promoted the level of caspases, Bax, AIF, Endo G, p21, PARP and p-p53. The expression level of Bcl-2 decreased in HCT-15 cells on incubation with 5 μM concentration of capecitabine.Conclusion: Capecitabine treatment causes inhibition of colon cancer growth via the mitochondrial pathway of apoptosis. Thus, capecitabine may have therapeutic application in colon carcinoma treatment.Keywords: Capecitabine, 5-Fluorouracil, Translocation, Colon cancer, Colitis, Apoptosi

Research on the Coordination Mechanism and Improvement Strategy of the Business Model from China’s Export Cross-border E-commerce ——Based on the Theory of Coevolution

As a new business model of e-commerce,export cross-border e-commerce has a great significance to promotesustainable development of domestic economy and meet the demands of foreign consumers. With rapid development of export cross-border e-commerce in recent years, many problems occur that hinder its development, such as shortage of relevant professionals and lack of the innovation on business model. The main reason is that the export cross-border e-commerce has attracted numerous participants, who prefer to enhance their competitiveness by any means to maximize their self-interest without considering the long-term development on a win-win basis. Thus, this article proposes that the participants can overcome their difficulties and gain the win-win goal by mutual benefits and mutual constraints based on the theory of coevolution, so as to promote the quick development of export cross-border e-commerce

The Analysis on Multimodal Transport Mode of Cross-border E-commerce with \u27the Belt and Road\u27 Strategy Based on Personalized Recommendation

With the further advance of \u27the Belt and Road\u27 strategy , China\u27s cross-border E-commerce has obtained powerful policy support and wide world market. But from the view of users\u27 coverage and total import and export of the trade along \u27the Belt and Road\u27 , China\u27s cross-border E-commerce still has great potential for development, while the high transportation cost is the main resistance in business. Therefore, based on the theory of customer personalized recommendation, combining with the successful cases of personalized services recommendation system from Jingdong and eBay, this article puts forward the multimodal transport service mode of China\u27s cross-border logistics enterprises so as to customize the optimized logistics service system for e-commerce and achieve a win-win situation for customers and enterprises

Highly sensitive magnetite nano clusters for MR cell imaging

High sensitivity and suitable sizes are essential for magnetic iron oxide contrast agents for cell imaging. In this study, we have fabricated highly MR sensitive magnetite nanoclusters (MNCs) with tunable sizes. These clusters demonstrate high MR sensitivity. Especially, water suspensions of the MNCs with average size of 63 nm have transverse relaxivity as high as 630 s-1mM-1, which is among the most sensitive iron oxide contrast agents ever reported. Importantly, such MNCs have no adverse effects on cells (RAW 264.7). When used for cell imaging, they demonstrate much higher efficiency and sensitivity than those of SHU555A (Resovist), a commercially available contrast agent, both in vitro and in vivo, with detection limits of 3,000 and 10,000 labeled cells, respectively. The studied MNCs are sensitive for cell imaging and promising for MR cell tracking in clinics

Identifying Expressway Accident Black Spots Based on the Secondary Division of Road Units

For the purpose of reducing the harm of expressway traffic accidents and improving the accuracy of traffic accident black spots identification, this paper proposes a method for black spots identification of expressway accidents based on road unit secondary division and empirical Bayes method. Based on the modelling ideas of expressway accident prediction models in HSM (Highway Safety Manual), an expressway accident prediction model is established as a prior distribution and combined with empirical Bayes method safety estimation to obtain a Bayes posterior estimate. The posterior estimated value is substituted into the quality control method to obtain the black spots identification threshold. Finally, combining the Xi\u27an-Baoji expressway related data and using the method proposed in this paper, a case study of Xibao Expressway is carried out, and sections 9, 19, and 25 of Xibao Expressway are identified as black spots. The results show that the method of secondary segmentation based on dynamic clustering can objectively describe the concentration and dispersion of accident spots on the expressway, and the proposed black point recognition method based on empirical Bayes method can accurately identify accident black spots. The research results of this paper can provide a basis for decision-making of expressway management departments, take targeted safety improvement measures

Sparse and low-rank techniques for the efficient restoration of images

Image reconstruction is a key problem in numerous applications of computer vision and medical imaging. By removing noise and artifacts from corrupted images, or by enhancing the quality of low-resolution images, reconstruction methods are essential to provide high-quality images for these applications. Over the years, extensive research efforts have been invested toward the development of accurate and efficient approaches for this problem. Recently, considerable improvements have been achieved by exploiting the principles of sparse representation and nonlocal self-similarity. However, techniques based on these principles often suffer from important limitations that impede their use in high-quality and large-scale applications. Thus, sparse representation approaches consider local patches during reconstruction, but ignore the global structure of the image. Likewise, because they average over groups of similar patches, nonlocal self-similarity methods tend to over-smooth images. Such methods can also be computationally expensive, requiring a hour or more to reconstruct a single image. Furthermore, existing reconstruction approaches consider either local patch-based regularization or global structure regularization, due to the complexity of combining both regularization strategies in a single model. Yet, such combined model could improve upon existing techniques by removing noise or reconstruction artifacts, while preserving both local details and global structure in the image. Similarly, current approaches rarely consider external information during the reconstruction process. When the structure to reconstruct is known, external information like statistical atlases or geometrical priors could also improve performance by guiding the reconstruction. This thesis addresses limitations of the prior art through three distinct contributions. The first contribution investigates the histogram of image gradients as a powerful prior for image reconstruction. Due to the trade-off between noise removal and smoothing, image reconstruction techniques based on global or local regularization often over-smooth the image, leading to the loss of edges and textures. To alleviate this problem, we propose a novel prior for preserving the distribution of image gradients modeled as a histogram. This prior is combined with low-rank patch regularization in a single efficient model, which is then shown to improve reconstruction accuracy for the problems of denoising and deblurring. The second contribution explores the joint modeling of local and global structure regularization for image restoration. Toward this goal, groups of similar patches are reconstructed simultaneously using an adaptive regularization technique based on the weighted nuclear norm. An innovative strategy, which decomposes the image into a smooth component and a sparse residual, is proposed to preserve global image structure. This strategy is shown to better exploit the property of structure sparsity than standard techniques like total variation. The proposed model is evaluated on the problems of completion and super-resolution, outperforming state-of-the-art approaches for these tasks. Lastly, the third contribution of this thesis proposes an atlas-based prior for the efficient reconstruction of MR data. Although popular, image priors based on total variation and nonlocal patch similarity often over-smooth edges and textures in the image due to the uniform regularization of gradients. Unlike natural images, the spatial characteristics of medical images are often restricted by the target anatomical structure and imaging modality. Based on this principle, we propose a novel MRI reconstruction method that leverages external information in the form of an probabilistic atlas. This atlas controls the level of gradient regularization at each image location, via a weighted total-variation prior. The proposed method also exploits the redundancy of nonlocal similar patches through a sparse representation model. Experiments on a large scale dataset of T1-weighted images show this method to be highly competitive with the state-of-the-art

Research on the Innovation of Business Ecosystem Model in China’s 0nline Food Reservation Market at Sharing Economic Era

At the sharing economy era, the online food reservation market has experienced great changes, such as the mobilization of ordering，cooperation of logistics , diversification of revenue stream. The ordering patterns has also changed from network order to improve user experience. At present, online food reservation market has difficulties inquickly dealing with the impacts and challenges bought by external environment due to lack of coordination and sharing mechanisms and competition over cooperation among economic individuals.Based on the theory of business ecosystem, this paper focuses on the impacts and challenges brought by the sharing economic era and takes “Huijiachifan” as a case study and proposes new framework of business ecosystem model in China\u27s online food reservation market