Competitive Strategy, Market Entry Mode and International Performance: The Case of Construction Firms in China

As an important participant in the international construction market, Chinese construction firms (CCFs) are confronted with the tasks of keeping themselves competitive. To help CCFs maintain and improve their competitiveness, this research builds a conceptual model to investigate the relationship between competitive strategy, market entry mode and performance within CCFs. Based on data collected from CCFs, this research has confirmed the importance of cost leadership strategy, differentiation strategy and business scope diversification, to achieve their superior performance. Moreover, there are positive relationships among entry mode strategies with CCFs’ international performance

Power frequency interference and suppression in measurement of power transmission tower grounding resistance

“If you want peace, work for justice.” – Pope Paul VI This paper explores how the children’s right to be heard is implemented in the criminal proceedings in Romania and Norway. The judicial practices in the two countries are analysed in relation to four elements identified in the literature as relevant to the child’s right to be heard- space, voice, audience and influence. The two juvenile justice systems are then compared to each other, as well as to international best practices, with the final aim of identifying small-scale measures worth disseminating in Romania and Norway to strengthen the effectiveness of child’s right to be heard. The paper argues that a more effective implementation of the children’s right to be heard strengthen all the array of the children’s rights, makes the juvenile justice system more child-friendly and facilitates the transition from conflict and punitive justice towards positive peace. Keywords: right of the child to be heard, juvenile justice, children’s rights, child-friendly justic

Second-order flows for approaching stationary points of a class of non-convex energies via convex-splitting schemes

The use of accelerated gradient flows is an emerging field in optimization, scientific computing and beyond. This paper contributes to the theoretical underpinnings of a recently-introduced computational paradigm known as second-order flows, which demonstrate significant performance particularly for the minimization of non-convex energy functionals defined on Sobolev spaces, and are characterized by novel dissipative hyperbolic partial differential equations. Our approach hinges upon convex-splitting schemes, a tool which is not only pivotal for clarifying the well-posedness of second-order flows, but also yields a versatile array of robust numerical schemes through temporal and spatial discretization. We prove the convergence to stationary points of such schemes in the semi-discrete setting. Further, we establish their convergence to time-continuous solutions as the time-step tends to zero, and perform a comprehensive error analysis in the fully discrete case. Finally, these algorithms undergo thorough testing and validation in approaching stationary points of non-convex variational models in applied sciences, such as the Ginzburg-Landau energy in phase-field modeling and a specific case of the Landau-de Gennes energy of the Q-tensor model for liquid crystals

CCR2 expression correlates with prostate cancer progression

Although the primary role of chemokines and their receptors is controlling the trafficking of leukocytes during inflammatory responses, they also play pleoitropic roles in cancer development. There is emerging evidence that cancer cells produce chemokines that induce tumor cell proliferation or chemotaxis in various cancer types. We have previously reported that MCP-1 acts as a paracrine and autocrine factor for prostate cancer (PCa) growth and invasion. As the cellular effects of MCP-1 are mediated by CC chemokine receptor 2 (CCR2), we hypothesized that CCR2 may contribute PCa progression. Accordingly, we first determined CCR2 mRNA and protein expression in various cancer cell lines, including PCa and other cancer types. All cells expressed CCR2 mRNA and protein, but in PCa, more aggressive cancer cells such as C4-2B, DU145, and PC3 expressed a higher amount of CCR2 compared with the less aggressive cancer cells such as LNCaP or non-neoplastic PrEC and RWPE-1 cells. Further, we found a positive correlation between CCR2 expression and PCa progression by analyzing an ONCOMINE gene array database. We confirmed that CCR2 mRNA was highly expressed in PCa metastatic tissues compared with the localized PCa or benign prostate tissues by real-time RT-PCR. Finally, CCR2 protein expression was examined by immunohistochemical staining on tissue microarray specimens from 96 PCa patients and 31 benign tissue controls. We found that CCR2 expression correlated with Gleason score and clinical pathologic stages, whereas lower levels of CCR2 were expressed in normal prostate tissues. These results suggest that CCR2 may contribute to PCa development. J. Cell. Biochem. 101: 676–685, 2007. © 2007 Wiley-Liss, Inc.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/56008/1/21220_ftp.pd

Bulletin (1942-1943)

https://red.mnstate.edu/bulletins/1023/thumbnail.jp

Towards Robust Visual Information Extraction in Real World: New Dataset and Novel Solution

Visual information extraction (VIE) has attracted considerable attention recently owing to its various advanced applications such as document understanding, automatic marking and intelligent education. Most existing works decoupled this problem into several independent sub-tasks of text spotting (text detection and recognition) and information extraction, which completely ignored the high correlation among them during optimization. In this paper, we propose a robust visual information extraction system (VIES) towards real-world scenarios, which is a unified end-to-end trainable framework for simultaneous text detection, recognition and information extraction by taking a single document image as input and outputting the structured information. Specifically, the information extraction branch collects abundant visual and semantic representations from text spotting for multimodal feature fusion and conversely, provides higher-level semantic clues to contribute to the optimization of text spotting. Moreover, regarding the shortage of public benchmarks, we construct a fully-annotated dataset called EPHOIE (https://github.com/HCIILAB/EPHOIE), which is the first Chinese benchmark for both text spotting and visual information extraction. EPHOIE consists of 1,494 images of examination paper head with complex layouts and background, including a total of 15,771 Chinese handwritten or printed text instances. Compared with the state-of-the-art methods, our VIES shows significant superior performance on the EPHOIE dataset and achieves a 9.01% F-score gain on the widely used SROIE dataset under the end-to-end scenario.Comment: 8 pages, 5 figures, to be published in AAAI 202