Comparison of Urban Form based on different city walls between Quanzhou and Newcastle upon Tyne

[EN] Quanzhou in south-eastern China was built in the Sui Dynasty, having more than 1,000 years of history. Its urban development led to the triple walls in a different period of time. Its unique landscape of multiple walls is a one of the Chinese ancient city patterns. However, the massive stone-built city wall pattern like Newcastle also has more than 1000, years of history in western cities .City walls maintain the preeminence as the city’s most powerful fixation line. The expansion of the wall in Quanzhou shows how the time-space changes, while Newcastle' s fringe belt is relatively stable, which forms a different urban form. This article mainly compares the following aspects: (1) The development of Quanzhou fringe belt; (2) Differences of fringe belts between the multiple walls city and the sole wall city; (3) Differences of land use in intramural zone between two cities. This paper analyzes the differences of fringe belts caused by city walls between Quanzhou, (China) and Newcastle, (England), and their influence on the urban form between the East and the West.This paper is co-funded by the Youth Program of the National Natural Science Foundation (51308232), the National Natural Science Foundation Projects (51578250), the National Science and Technology Support Program of the 12th Five-Year Plan (2015BAL01B01), the Social Development Guidance Project of Fujian Province (2015Y037), the Natural Science Foundation of Fujian Province (2016J01238), Science and Technology Innovation Fund for Young Teachers of Huaqiao University (ZQNPY213).Subsidized Project for Cultivating Postgraduates Innovatives Ability in Scientific Research of Huaqiao UniversityWang, D.; Zheng, J. (2018). Comparison of Urban Form based on different city walls between Quanzhou and Newcastle upon Tyne. En 24th ISUF International Conference. Book of Papers. Editorial Universitat Politècnica de València. 167-175. https://doi.org/10.4995/ISUF2017.2017.5061OCS16717

Angular distribution in two-photon double ionization of helium by intense attosecond soft X-ray pulses

We investigate two-photon double ionization of helium by intense ($10^{15} W/cm^2$) ultrashort ($\approx 300$ as) soft X-ray pulses (E = 91.6 eV). The time-dependent two-electron Schr\"odinger equation is solved using a coupled channel method. We show that for ultrashort pulses the angular distribution of ejected electrons depends on the pulse duration and provides novel insights into the role of electron correlations in the two-electron photoemission process. The angular distribution at energies near the ``independent electron'' peaks is close to dipolar while it acquires in the ``valley'' of correlated emission a significant quadrupolar component within a few hundred attoseconds.Comment: 17 pages, 6 fig

A Personalized Commodities Recommendation Procedure and Algorithm Based on Association Rule Mining

The double-quick growth of EB has caused commodities overload, where our customers are not longer able to efficiently choose the products adapt to them. In order to overcome the situation that both companies and customers are facing, we present a personalized recommendation, although several recommendation systems which may have some disadvantages have been developed. In this paper, we focus on the association rule mining by EFFICIENT algorithm which can simple discovery rapidly the all association rules without any information loss. The EFFICIENT algorithm which comes of the conventional Aprior algorithm integrates the notions of fast algorithm and predigested algorithm to find the interesting association rules in a given transaction data sets. We believe that the procedure should be accepted, and experiment with real-life databases show that the proposed algorithm is efficient one

MGCN: Medical Relation Extraction Based on GCN

With the progress of society and the improvement of living standards, people pay more and more attention to personal health, and WITMED (Wise Information Technology of med) has occupied an important position. The relationship prediction work in the medical field has high requirements on the interpretability of the method, but the relationship between medical entities is complex, and the existing methods are difficult to meet the requirements. This paper proposes a novel medical information relation extraction method MGCN, which combines contextual information to provide global interpretability for relation prediction of medical entities. The method uses Co-occurrence Graph and Graph Convolutional Network to build up a network of relations between entities, uses the Open-world Assumption to construct potential relations between associated entities, and goes through the Knowledge-aware Attention mechanism to give relation prediction for the entity pair of interest. Experiments were conducted on a public medical dataset CTF, MGCN achieved the score of 0.831, demonstrating its effectiveness in medical relation extraction

Mega-Reward: Achieving Human-Level Play without Extrinsic Rewards

Intrinsic rewards were introduced to simulate how human intelligence works; they are usually evaluated by intrinsically-motivated play, i.e., playing games without extrinsic rewards but evaluated with extrinsic rewards. However, none of the existing intrinsic reward approaches can achieve human-level performance under this very challenging setting of intrinsically-motivated play. In this work, we propose a novel megalomania-driven intrinsic reward (called mega-reward), which, to our knowledge, is the first approach that achieves human-level performance in intrinsically-motivated play. Intuitively, mega-reward comes from the observation that infants' intelligence develops when they try to gain more control on entities in an environment; therefore, mega-reward aims to maximize the control capabilities of agents on given entities in a given environment. To formalize mega-reward, a relational transition model is proposed to bridge the gaps between direct and latent control. Experimental studies show that mega-reward (i) can greatly outperform all state-of-the-art intrinsic reward approaches, (ii) generally achieves the same level of performance as Ex-PPO and professional human-level scores, and (iii) has also a superior performance when it is incorporated with extrinsic rewards

Quantal And Classical Correspondence Of Double Scattering

Electron emission from atom-atom collisions is analyzed within the framework, of both quantal and classical dynamics. We examine the effect of explicit electron-electron (e-e) interactions on the ejected electron spectra in hard collisions involving simultaneous excitation and ionization in the collision of two structured atoms. A double scattering sequence represented by a second order Bom approximation has been shown to give a dominant contribution over the single scattering to projectile ionization. A classical simulation confirms the double scattering process is analogous to the Thomas two-step capture mechanism. We find good agreement between quantal and classical calculations, showing the convergence of the Bom series to second order and the possibility of a classical treatment for e-e interactions in non-perturbative regimes. We also find that the shape of the ejected electron spectrum is very different from the usually assumed Lorentzian distribution. © 1993 IOP Publishing Ltd

ResShift: Efficient Diffusion Model for Image Super-resolution by Residual Shifting

Diffusion-based image super-resolution (SR) methods are mainly limited by the low inference speed due to the requirements of hundreds or even thousands of sampling steps. Existing acceleration sampling techniques inevitably sacrifice performance to some extent, leading to over-blurry SR results. To address this issue, we propose a novel and efficient diffusion model for SR that significantly reduces the number of diffusion steps, thereby eliminating the need for post-acceleration during inference and its associated performance deterioration. Our method constructs a Markov chain that transfers between the high-resolution image and the low-resolution image by shifting the residual between them, substantially improving the transition efficiency. Additionally, an elaborate noise schedule is developed to flexibly control the shifting speed and the noise strength during the diffusion process. Extensive experiments demonstrate that the proposed method obtains superior or at least comparable performance to current state-of-the-art methods on both synthetic and real-world datasets, even only with 15 sampling steps. Our code and model are available at https://github.com/zsyOAOA/ResShift.Comment: 17 pages, 7 figure

Hydrothermal synthesis of MnO2/CNT nanocomposite with a CNT core/porous MnO2 sheath hierarchy architecture for supercapacitors

MnO2/carbon nanotube [CNT] nanocomposites with a CNT core/porous MnO2 sheath hierarchy architecture are synthesized by a simple hydrothermal treatment. X-ray diffraction and Raman spectroscopy analyses reveal that birnessite-type MnO2 is produced through the hydrothermal synthesis. Morphological characterization reveals that three-dimensional hierarchy architecture is built with a highly porous layer consisting of interconnected MnO2 nanoflakes uniformly coated on the CNT surface. The nanocomposite with a composition of 72 wt.% (K0.2MnO2·0.33 H2O)/28 wt.% CNT has a large specific surface area of 237.8 m2/g. Electrochemical properties of the CNT, the pure MnO2, and the MnO2/CNT nanocomposite electrodes are investigated by cyclic voltammetry and electrochemical impedance spectroscopy measurements. The MnO2/CNT nanocomposite electrode exhibits much larger specific capacitance compared with both the CNT electrode and the pure MnO2 electrode and significantly improves rate capability compared to the pure MnO2 electrode. The superior supercapacitive performance of the MnO2/CNT nancomposite electrode is due to its high specific surface area and unique hierarchy architecture which facilitate fast electron and ion transport