The creative industrial park : formation path and evolution mechanism

This paper has built a three-stage assumption of creative industrial park on the base of evolutionary economics, which are the gather of units, the construction of interface and the development of network. The gather of units is a reflection of resource search, the construction of interface is a need of identity, and the development of network is a result of multi-dimensional expansion.In the three-stage evolution, the creative industrial park increases constantly their evolution level from the simple geographic gathered to the division and cooperation of labor, until the formation of novel systems. Then this paper analyzes the 798 creative industrial park using the three-stage assumption. This paper finds the main problem of 798’s self-destructing after the low level development of the third stage is the exclusion of the commercial prosperity to the art production. Accordingly,the paper puts forword four modes of promoting the integration between art and commerce. At last, this paper argues the different characteristics of the creative industrial park from other industrial parks. On the angle of formation path, the essence of creative industries is integration of culture and economy, technology. On the angle of evolution mechanism, it reflects novel characteristic of unit, identity characteristic of interface, and co-creation characteristic of network.creative industrial park; formation path; evolution mechanism; integration of culture,economy,and technology

Semaphorin 4D Promotes Skeletal Metastasis in Breast Cancer.

Bone density is controlled by interactions between osteoclasts, which resorb bone, and osteoblasts, which deposit it. The semaphorins and their receptors, the plexins, originally shown to function in the immune system and to provide chemotactic cues for axon guidance, are now known to play a role in this process as well. Emerging data have identified Semaphorin 4D (Sema4D) as a product of osteoclasts acting through its receptor Plexin-B1 on osteoblasts to inhibit their function, tipping the balance of bone homeostasis in favor of resorption. Breast cancers and other epithelial malignancies overexpress Sema4D, so we theorized that tumor cells could be exploiting this pathway to establish lytic skeletal metastases. Here, we use measurements of osteoblast and osteoclast differentiation and function in vitro and a mouse model of skeletal metastasis to demonstrate that both soluble Sema4D and protein produced by the breast cancer cell line MDA-MB-231 inhibits differentiation of MC3T3 cells, an osteoblast cell line, and their ability to form mineralized tissues, while Sema4D-mediated induction of IL-8 and LIX/CXCL5, the murine homologue of IL-8, increases osteoclast numbers and activity. We also observe a decrease in the number of bone metastases in mice injected with MDA-MB-231 cells when Sema4D is silenced by RNA interference. These results are significant because treatments directed at suppression of skeletal metastases in bone-homing malignancies usually work by arresting bone remodeling, potentially leading to skeletal fragility, a significant problem in patient management. Targeting Sema4D in these cancers would not affect bone remodeling and therefore could elicit an improved therapeutic result without the debilitating side effects

Dual Long Short-Term Memory Networks for Sub-Character Representation Learning

Characters have commonly been regarded as the minimal processing unit in Natural Language Processing (NLP). But many non-latin languages have hieroglyphic writing systems, involving a big alphabet with thousands or millions of characters. Each character is composed of even smaller parts, which are often ignored by the previous work. In this paper, we propose a novel architecture employing two stacked Long Short-Term Memory Networks (LSTMs) to learn sub-character level representation and capture deeper level of semantic meanings. To build a concrete study and substantiate the efficiency of our neural architecture, we take Chinese Word Segmentation as a research case example. Among those languages, Chinese is a typical case, for which every character contains several components called radicals. Our networks employ a shared radical level embedding to solve both Simplified and Traditional Chinese Word Segmentation, without extra Traditional to Simplified Chinese conversion, in such a highly end-to-end way the word segmentation can be significantly simplified compared to the previous work. Radical level embeddings can also capture deeper semantic meaning below character level and improve the system performance of learning. By tying radical and character embeddings together, the parameter count is reduced whereas semantic knowledge is shared and transferred between two levels, boosting the performance largely. On 3 out of 4 Bakeoff 2005 datasets, our method surpassed state-of-the-art results by up to 0.4%. Our results are reproducible, source codes and corpora are available on GitHub.Comment: Accepted & forthcoming at ITNG-201

CP violation in lepton-number-conserving processes through heavy Majorana neutrinos at future lepton colliders

Small neutrino masses confirmed in the neutrino oscillation experiments indicate the need for new physics beyond the standard model. Seesaw mechanism is an interesting way to extend the standard model for explaining the neutrino masses. In a low-scale type-I seesaw mechanism, the tiny masses of neutrinos can be explained by heavy Majorana neutrino masses. Heavy Majorana neutrinos can lead to lepton-number-violating processes and the induced CP violation can contribute to the baryon asymmetry in the Universe. Heavy Majorana neutrinos can also lead to lepton-number-conserving processes and in this paper, we study the CP violation in lepton-number-conserving processes through heavy Majorana neutrinos at future lepton colliders. New possible observations of CP violation can also be connected to evidences of new physics beyond the standard model.Comment: 14 pages, 7 figure