Industrial Agglomeration, Production Networks and FDI Promotion The Case Study of China

Chinas Industrial clustering is a distinguished economic phenomenon over the last 20 years. It began to enter into its fast track in the mid-1990s and developed rapidly in recent years. Both market-driven force and government-driven force contribute to Chinese industrial clusters. The opening and stable macroeconomic policies create a favorable climate for the industrial clustering. Local government has made its contribution to construction on both hardware and software environments for industrial clusters. The major contribution of FDI to the local industrial clustering lies in helping integrating Chinese domestic industries into international division of labor and at the same time forging a relatively integrated production chain for Chinese domestic industries. At present, China has stepped into the new phase of industrial clusters upgrading. Chinese government is gradually improving the local software infrastructure for industry clustering.Industrial Agglomeration, China, Production Networks, FDI, foreign direct investment

Sub-wavelength Coherent Imaging of a Pure-Phase Object with Thermal Light

We report, for the first time, the observation of sub-wavelength coherent image of a pure phase object with thermal light,which represents an accurate Fourier transform. We demonstrate that ghost-imaging scheme (GI) retrieves amplitude transmittance knowledge of objects rather than the transmitted intensities as the HBT-type imaging scheme does.Comment: 5 pages, 4 figures; Any comments pls. contact: [email protected]

Learning to Augment for Data-Scarce Domain BERT Knowledge Distillation

Despite pre-trained language models such as BERT have achieved appealing performance in a wide range of natural language processing tasks, they are computationally expensive to be deployed in real-time applications. A typical method is to adopt knowledge distillation to compress these large pre-trained models (teacher models) to small student models. However, for a target domain with scarce training data, the teacher can hardly pass useful knowledge to the student, which yields performance degradation for the student models. To tackle this problem, we propose a method to learn to augment for data-scarce domain BERT knowledge distillation, by learning a cross-domain manipulation scheme that automatically augments the target with the help of resource-rich source domains. Specifically, the proposed method generates samples acquired from a stationary distribution near the target data and adopts a reinforced selector to automatically refine the augmentation strategy according to the performance of the student. Extensive experiments demonstrate that the proposed method significantly outperforms state-of-the-art baselines on four different tasks, and for the data-scarce domains, the compressed student models even perform better than the original large teacher model, with much fewer parameters (only ${\sim}13.3\%$) when only a few labeled examples available.Comment: AAAI202

Interface engineering of mesoporous triphasic cobalt-copper phosphides as active electrocatalysts for overall water splitting

Efficient electrocatalysts for water splitting are essential for viable generation of highly purified hydrogen. Hence there is a need to develop robust catalysts to eliminate barriers associated with sluggish kinetics associated with both anodic oxygen and cathodic hydrogen evolution reactions. Herein, we report a two-step nanocasting-solid phase phosphorization approach to generate ordered mesoporous triphasic phosphides CoP@Cu2P-Cu3P. We show that it is a highly efficient bifunctional electrocatalyst useful for overall water splitting. The mesoporous triphasic CoP@Cu2P-Cu3P only requires a low overpotential of 255 mV and 188 mV to achieve 10 mA cm(-2) for oxygen and hydrogen evolution reactions, respectively. The combination of mesoporous pores (similar to 5.6 nm) with very thin walls (similar to 3.7 nm) and conductive networks in triphasic CoP@Cu2P-Cu3P enable rapid rate of electron transfer and mass transfer. In addition, when CoP@Cu2P-Cu3P is used to fabricate symmetric electrodes, the high surface area mesoporous structure and synergetic effects between phases together contribute to a low cell voltage of 1.54 V to drive a current density 10 mA cm(-2). This performance is superior to noble-metal-based Pt/C-IrO2/C. This work provides a new approach for the facile design and application of multiphase phosphides as highly active bifunctional and stable electrocatalysts for water-alkali electrolyzers

Observation of Temperature-Induced Crossover to an Orbital-Selective Mott Phase in Ax_{x}Fe2−y_{2-y}Se2_2 (A=K, Rb) Superconductors

In this work, we study the A$_{x}$Fe$_{2-y}$Se$_2$ (A=K, Rb) superconductors using angle-resolved photoemission spectroscopy. In the low temperature state, we observe an orbital-dependent renormalization for the bands near the Fermi level in which the dxy bands are heavily renormliazed compared to the dxz/dyz bands. Upon increasing temperature to above 150K, the system evolves into a state in which the dxy bands have diminished spectral weight while the dxz/dyz bands remain metallic. Combined with theoretical calculations, our observations can be consistently understood as a temperature induced crossover from a metallic state at low temperature to an orbital-selective Mott phase (OSMP) at high temperatures. Furthermore, the fact that the superconducting state of A$_{x}$Fe$_{2-y}$Se$_2$ is near the boundary of such an OSMP constraints the system to have sufficiently strong on-site Coulomb interactions and Hund's coupling, and hence highlight the non-trivial role of electron correlation in this family of iron superconductors