Knowledge-based industry and regional growth

One of the most important but less understood phenomena in the beginning of the 21st century has been a shift toward knowledge-based economic activity in the comparative advantage of modern industrialized countries. Two broad trends has been observed in the global economy. That is, the output from the world's science and technology system has been growing rapidly and the nature of investment has been changed (MILLER, 1996). The relative proportions of physical and intangible investment have changed considerably with the relative increase of intangible investments since the 1980s. In addition, there has been increased complementarity between physical and intangible investments and more important role of high technology in both kinds of investment (MILLER, 1996). Even in the newly industrialized countries, the growth of technology intensive industries, the increase of R&D activities and the growth of the knowledge intensive producer services have been common feature in recent years. In this change of the structure of productive assets, the role of knowledge is well recognized as the most fundamental resources in recent years (OECD, 1996; WORLD BANK, 1998). The development of information and communication technology (ICT) and globalisation trend have promoted this shift toward knowledge-based economy

Parareal Neural Networks Emulating a Parallel-in-time Algorithm

As deep neural networks (DNNs) become deeper, the training time increases. In this perspective, multi-GPU parallel computing has become a key tool in accelerating the training of DNNs. In this paper, we introduce a novel methodology to construct a parallel neural network that can utilize multiple GPUs simultaneously from a given DNN. We observe that layers of DNN can be interpreted as the time step of a time-dependent problem and can be parallelized by emulating a parallel-in-time algorithm called parareal. The parareal algorithm consists of fine structures which can be implemented in parallel and a coarse structure which gives suitable approximations to the fine structures. By emulating it, the layers of DNN are torn to form a parallel structure which is connected using a suitable coarse network. We report accelerated and accuracy-preserved results of the proposed methodology applied to VGG-16 and ResNet-1001 on several datasets

Balanced Group Convolution: An Improved Group Convolution Based on Approximability Estimates

The performance of neural networks has been significantly improved by increasing the number of channels in convolutional layers. However, this increase in performance comes with a higher computational cost, resulting in numerous studies focused on reducing it. One promising approach to address this issue is group convolution, which effectively reduces the computational cost by grouping channels. However, to the best of our knowledge, there has been no theoretical analysis on how well the group convolution approximates the standard convolution. In this paper, we mathematically analyze the approximation of the group convolution to the standard convolution with respect to the number of groups. Furthermore, we propose a novel variant of the group convolution called balanced group convolution, which shows a higher approximation with a small additional computational cost. We provide experimental results that validate our theoretical findings and demonstrate the superior performance of the balanced group convolution over other variants of group convolution.Comment: 26pages, 2 figure

The involvement of AMPK/GSK3-beta signals in the control of metastasis and proliferation in hepato-carcinoma cells treated with anthocyanins extracted from Korea wild berry Meoru

BACKGROUND: Activation of the Wnt pathway is known to promote tumorigenesis and tumor metastasis, and targeting Wnt pathway inhibition has emerged as an attractive approach for controlling tumor invasion and metastasis. The major pathway for inhibiting Wnt is through the degradation of β-catenin by the GSK3-beta/CK1/Axin/APC complex. It was found that Hep3B hepato-carcinoma cells respond to anthocyanins through GSK3-beta-induced suppression of beta-catenin; however, they cannot dephosphorylate GSK3-beta without AMPK activation. METHODS: We tested the effects of anthocyanins on proliferation and apoptosis by MTT and Annexin V-PI staining in vitro. Mouse xenograft models of hepato-carcinomas were established by inoculation with Hep3B cells, and mice were injected with 50 mg/kg/ml of anthocyanins. In addition, protein levels of p-GSK3-beta, beta-catenin, p-AMPK, MMP-9, VEGF, and Ang-1 were also analyzed using western blot. RESULTS: Anthocyanins decrease phospho-GSK3-beta and beta-catenin expression in an in vivo tumor xenograft model, increase AMPK activity in this model, and inhibit cell migration and invasion, possibly by inhibiting MMP-2 (in vitro) and the panendothelial marker, CD31 (in vivo). To elucidate the role of the GSK3-beta/beta-catenin pathway in cancer control, we conditionally inactivated this pathway, using activated AMPK for inhibition. Further, we showed that AMPK siRNA treatment abrogated the ability of anthocyanins to control cell proliferation and metastatic potential, and Compound C, an AMPK inhibitor, could not restore GSK3-beta regulation, as exhibited by anthocyanins in Hep3B cells. CONCLUSION: These observations imply that the AMPK-mediated GSK3-beta/beta-catenin circuit plays crucial roles in inhibiting cancer cell proliferation and metastasis in anthocyanin-treated hepato-carcinoma cells of Meoru origin

Growth responses of Escherichia coli and Myxococcus xanthus on agar gel substrates with different levels of stiffness

Bacteria colonize surfaces responding to the physicochemical properties of substrates. A systematic study was carried out with growing single bacterial colonies on the surface of agar media to decipher the interaction between bacterial growth and substrate stiffness. We investigated the growth kinetics of wild-type Escherichia coli, non-motile E. coli, and Myxococcus xanthus, cultured on semi-solid agar substrates containing different amounts of nutrient and agar. We found that substrate stiffness, which was controlled by agar concentration, modulates the growth of motile bacteria, such as wild-type E. coli and M. xanthus, independently of the nutrient level, but does not affect the growth response of non-motile E. coli. Interestingly, growth of M. xanthus moving with type IV pili correlates negatively with the substrate stiffness in contrast to wild-type E. coli propelled by flagella. The present study demonstrates that the type of surface motility is a key  determinant of the growth response of bacteria to substrate stiffness, and has potential application to the design of surfaces that prevent or promote biofilm formation.Key words: Bacterial colonization, substrate stiffness, surface motility, swarming, Escherichia coli, Myxococcus xanthus