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Automatic Term Extraction (ATE) deals with the extraction of terminology from a domain specific corpus, and has long been an established research area in data and knowledge acquisition. ATE remains a challenging task as it is know...
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Automatic Term Extraction (ATE) deals with the extraction of terminology from a domain specific corpus, and has long been an established research area in data and knowledge acquisition. ATE remains a challenging task as it is known that there is no existing ATE methods that can consistently outperform others in any domain. This work adopts a refreshed perspective to this problem: instead of searching for such a 'one-size-fit-all' solution that may never exist, we propose to develop generic methods to 'enhance' existing ATE methods. We introduce SemRe-Rank, the first method based on this principle, to incorporate semantic relatedness-an often overlooked venue-into an existing ATE method to further improve its performance. SemRe-Rank incorporates word embeddings into a personalised PageRank process to compute 'semantic importance' scores for candidate terms from a graph of semantically related words (nodes), which are then used to revise the scores of candidate terms computed by a base ATE algorithm. Extensively evaluated with 13 state-of-the-art base ATE methods on four datasets of diverse nature, it is shown to have achieved widespread improvement over all base methods and across all datasets, with up to 15 percentage points when measured by the Precision in the top ranked K candidate terms (the average for a set of K's), or up to 28 percentage points in F1 measured at a K that equals to the expected real terms in the candidates (F1 in short). Compared to an alternative approach built on the well-known TextRank algorithm, SemRe-Rank can potentially outperform by up to 8 points in Precision at top K, or up to 17 points in F1.
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In this paper, the key intention is to present a compact and efficient MATLAB code for the implementation of the isogeometric topology optimization (ITO) method published by Jie Gao et al. (Int J Numer Methods Eng 119: 991-1017, 2...
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In this paper, the key intention is to present a compact and efficient MATLAB code for the implementation of the isogeometric topology optimization (ITO) method published by Jie Gao et al. (Int J Numer Methods Eng 119: 991-1017, 2019). A main function IgaTop2D with eight inputs in the 56-line MATLAB code is developed, mainly including nine components: (1) Geom_Mod subfunction that uses non-uniform rational B-splines (NURBS) to develop the geometrical model; (2) the preparation of the isogeometric analysis (IGA) that is implemented in Pre_IGA subfunction; (3) the definition of Dirichlet and Neumann boundary conditions in Boun_Cond subfunction; (4) the initialization of control densities and the densities at Gauss quadrature points implemented from lines 11 to 20 of the main function; (5) a Shep_Fun subfunction for the smoothing mechanism; (6) IGA to solve structural responses in three steps: compute IGA element stiffness matrices in Stiff_Ele2D subfunction, assemble all IGA element stiffness matrices in Stiff_Ass2D subfunction, and Solving; (7) calculation of the objective function and sensitivity analysis in lines 32-46 of IgaTop2D; (8) OC to advance design variables; and (9) the representations of the optimized solutions in Plot_Data and Plot_Topy subfunctions. Finally, several numerical examples are shown to demonstrate the effectiveness of the ITO MATLAB implementation IgaTop2D, which are attached in the Appendix, also offering an entry point for newcomers who have an interest in the field of the ITO.
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Auxetic composites, a kind of rationally artificial materials, possess superior multifunctional properties due to a mixture of materials. In this paper, an Isogeometric Topology Optimization (ITO) method is proposed for computatio...
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Auxetic composites, a kind of rationally artificial materials, possess superior multifunctional properties due to a mixture of materials. In this paper, an Isogeometric Topology Optimization (ITO) method is proposed for computational design of both the re-entrant and chiral auxetic composites in both 2D and 3D. The homogenization is numerically implemented using isogeometric analysis (IGA) to predict macroscopic effective properties of microstructures, where the periodic boundary formulation is imposed. An effective Non-Uniform Rational B-splines (NURBS)-based Multi-Material Interpolation (N-MMI) model is applied to compute material properties of all points in composite microstructures, mainly including the Fields of Design Variables (DVFs), Fields of Topology Variables (TVFs), and multi-material interpolation. A unified ITO formulation is developed for 2D and 3D auxetic composites, where an appropriate objective function with a weight parameter is defined to control the generation of different deformation mechanisms. Finally, several numerical examples are performed to demonstrate the effectiveness of the proposed ITO method, and a series of 2D and 3D auxetic composites with the re-entrant and chiral deformation mechanisms are found. The optimized composite structures are simulated using ANSYS to show the auxetic behavior. (C) 2020 Elsevier B.V. All rights reserved.
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In November 2018, CEPC CDR was announced and since then, CEPC accelerator entered TDR phase towards its planned completion at the end of 2022. In this paper, we give status review of CEPC optimization design, hardware TDR R&D progresses, CEPC-SppC compatibility relation, civil engineering design, site selection, CIPC and international collaborations, etc. CEPC plan is also presented....
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In November 2018, CEPC CDR was announced and since then, CEPC accelerator entered TDR phase towards its planned completion at the end of 2022. In this paper, we give status review of CEPC optimization design, hardware TDR R&D progresses, CEPC-SppC compatibility relation, civil engineering design, site selection, CIPC and international collaborations, etc. CEPC plan is also presented.
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Studies on gaming have made fruitful progress in diagnosing the problem and offering prescriptions for its mitigation. However, little is known about the actual reform efforts to curb gaming and the effectiveness of these strategi...
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Studies on gaming have made fruitful progress in diagnosing the problem and offering prescriptions for its mitigation. However, little is known about the actual reform efforts to curb gaming and the effectiveness of these strategies. This study contributes to the existing literature by examining the challenges of and strategies for mitigating distortion of performance data in Chinese local government in the past decade or so. It argues that curbing pernicious gaming such as information distortion is an uphill battle because it comes with a heavy political cost. In China, tackling the root cause of information distortion would jeopardize the key function of performance measurement, which is to ensure local compliance with the policy goals set by the authorities at the upper levels. Therefore, information distortion is selectively tackled and also selectively tolerated. This is achieved by concentrating on reducing distortion of key performance data that is vital for policymaking through strategies such as strengthening the state's ability to collect raw data directly and building up accountability in the statistical system. This study shows that those engaged in fighting gaming must make a tradeoff between reaping the benefits of performance management and reducing its associated risks.
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Two-dimensional (2D) materials have been the focus of materials research for many years due to their unique fascinating properties and large specific surface area (SSA). They are very sensitive to the analytes (ions, glucose, DNA,...
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Two-dimensional (2D) materials have been the focus of materials research for many years due to their unique fascinating properties and large specific surface area (SSA). They are very sensitive to the analytes (ions, glucose, DNA, protein, etc.), resulting in their wide-spread development in the field of sensing. New 2D materials, as the basis of applications, are constantly being fabricated and comprehensively studied. In a variety of sensing applications, the solution-gated transistor (SGT) is a promising biochemical sensing platform because it can work at low voltage in different electrolytes, which is ideal for monitoring body fluids in wearable electronics, e-skin, or implantable devices. However, there are still some key challenges, such as device stability and reproducibility, that must be faced in order to pave the way for the development of cost-effective, flexible, and transparent SGTs with 2D materials. In this review, the device preparation, device physics, and the latest application prospects of 2D materials-based SGTs are systematically presented. Besides, a bold perspective is also provided for the future development of these devices.
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This paper presents the compact and efficient Matlab codes for the concurrent topology optimization of multiscale composite structures not only in 2D scenario but also considering 3D cases. A modified SIMP approach (Sigmund 2007) ...
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This paper presents the compact and efficient Matlab codes for the concurrent topology optimization of multiscale composite structures not only in 2D scenario but also considering 3D cases. A modified SIMP approach (Sigmund 2007) is employed to implement the concurrent topological design, with an energy-based homogenization method (EBHM) to evaluate the macroscopic effective properties of the microstructure. The 2D and 3D Matlab codes in the paper are developed, using the 88-line 2D SIMP code (Struct Multidisc Optim 43(1): 1-16, 2011) and the 169-line 3D topology optimization code (Struct Multidisc Optim 50(6): 1175-1196, 2014), respectively. This paper mainly contributes to the following four aspects: (1) the code architecture for the topology optimization of cellular composite structures (ConTop2D.m and ConTop3D.m), (2) the code to compute the 3D iso-parametric element stiffness matrix (elementMatVec3D.m), (3) the EBHM to predict the macroscopic effective properties of 2D and 3D material microstructures (EBHM2D.m and EBHM3D.m), and (4) the code to calculate the sensitivities of the objective function with respect to the design variables at two scales. Several numerical examples are tested to demonstrate the effectiveness of the Matlab codes, which are attached in the Appendix, also offering an entry point for new comers in designing cellular composites using topology optimization.
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This paper examines the effect of customer geographic proximity on supplier tax avoidance. Based on 5135 Chinese firm–year observations from 2009 to 2020, we find a positive association between customer geographic distance and su...
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This paper examines the effect of customer geographic proximity on supplier tax avoidance. Based on 5135 Chinese firm–year observations from 2009 to 2020, we find a positive association between customer geographic distance and supplier tax avoidance. Moreover, this association is robust after studying endogeneity concerns. We further find that information asymmetry and detection risk are underlying mechanisms. We also find that this positive relation is more pronounced in suppliers with high financial risk, competitive industrial sectors, and weak marketization environments. Overall, our findings suggest that customer geographic localities within a country are an important factor affecting a supplier’s motivation for tax avoidance. Our research sheds light on how the change in a supplier’s information environment caused by differences in customer geographic proximity impacts its tax strategy.
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In this tutorial paper, we look into the evolution and prospect of network architecture and propose a novel conceptual architecture for the 6th generation (6G) networks. The proposed architecture has two key elements, i.e., holist...
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In this tutorial paper, we look into the evolution and prospect of network architecture and propose a novel conceptual architecture for the 6th generation (6G) networks. The proposed architecture has two key elements, i.e., holistic network virtualization and pervasive artificial intelligence (AI). The holistic network virtualization consists of network slicing and digital twin, from the aspects of service provision and service demand, respectively, to incorporate service-centric and user-centric networking. The pervasive network intelligence integrates AI into future networks from the perspectives of networking for AI and AI for networking, respectively. Building on holistic network virtualization and pervasive network intelligence, the proposed architecture can facilitate three types of interplay, i.e., the interplay between digital twin and network slicing paradigms, between model-driven and data-driven methods for network management, and between virtualization and AI, to maximize the flexibility, scalability, adaptivity, and intelligence for 6G networks. We also identify challenges and open issues related to the proposed architecture. By providing our vision, we aim to inspire further discussions and developments on the potential architecture of 6G.
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Graded lattice sandwich structures (GLSSs) enable superior structural performances due to the continuously-varying configurations and properties of lattices in space. This paper proposes a design method for GLSSs by multiscale top...
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Graded lattice sandwich structures (GLSSs) enable superior structural performances due to the continuously-varying configurations and properties of lattices in space. This paper proposes a design method for GLSSs by multiscale topology optimization. In this method, the geometrical configuration of a prototype lattice cell (PLC) is described by an explicit topology description function (TDF). Based on some sample lattice cells, a Kriging metamodel is constructed to predict the effective property of each lattice cell. Based on the Kriging metamodel, the thickness optimization of two solid face-sheets and the distribution optimization of lattice cells in core layer are respectively implemented. Driven by their equivalent densities, the configurations of lattice cells with similar topological features are generated by interpolating the shape of the PLC. Then, the graded lattice cells (GLCs) are generated. Using the proposed method, the computational burden involved in design of GLSSs can be reduced significantly. What is more, the manufacturability of GLSSs can be guaranteed by constructing a proper PLC with the help of TDF. Numerical examples in terms of compliance and natural frequency optimization of GLSSs are provided to verify the advantages of the proposed method. Also, bending tests are performed on the GLSSs fabricated by additive manufacturing (AM). The results reveal that GLSSs are stiffer and have larger natural frequencies than the uniform lattice sandwich structures. (C) 2021 Elsevier B.V. All rights reserved.
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