Relevant bibliographies by topics / Density embedding

Academic literature on the topic 'Density embedding'

Author: Grafiati
Published: 10 December 2022
Last updated: 29 January 2023

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Journal articles on the topic "Density embedding"

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Knizia, Gerald, and Garnet Kin-Lic Chan. "Density Matrix Embedding: A Strong-Coupling Quantum Embedding Theory." Journal of Chemical Theory and Computation 9, no. 3 (February 21, 2013): 1428–32. http://dx.doi.org/10.1021/ct301044e.

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Ye, Hong-Zhou, Matthew Welborn, Nathan D. Ricke, and Troy Van Voorhis. "Incremental embedding: A density matrix embedding scheme for molecules." Journal of Chemical Physics 149, no. 19 (November 21, 2018): 194108. http://dx.doi.org/10.1063/1.5053992.

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Džamonja, Mirna. "Isomorphic Universality and the Number of Pairwise Nonisomorphic Models in the Class of Banach Spaces." Abstract and Applied Analysis 2014 (2014): 1–11. http://dx.doi.org/10.1155/2014/184071.

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We develop the framework ofnatural spacesto study isomorphic embeddings of Banach spaces. We then use it to show that a sufficient failure of the generalized continuum hypothesis implies that the universality number of Banach spaces of a given density under a certain kind of positive embedding (very positive embedding) is high. An example of a very positive embedding is a positive onto embedding betweenC(K)andCLfor 0-dimensionalKandLsuch that the following requirement holds for allh≠0andf≥0inC(K): if0≤Th≤Tf, then there are constantsa≠0andbwith0≤a·h+b≤fanda·h+b≠0.
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Artiukhin, Denis G., Christoph R. Jacob, and Johannes Neugebauer. "Excitation energies from frozen-density embedding with accurate embedding potentials." Journal of Chemical Physics 142, no. 23 (June 21, 2015): 234101. http://dx.doi.org/10.1063/1.4922429.

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Laricchia, S., E. Fabiano, and F. Della Sala. "Frozen density embedding with hybrid functionals." Journal of Chemical Physics 133, no. 16 (October 28, 2010): 164111. http://dx.doi.org/10.1063/1.3494537.

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Culpitt, Tanner, Kurt R. Brorsen, Michael V. Pak, and Sharon Hammes-Schiffer. "Multicomponent density functional theory embedding formulation." Journal of Chemical Physics 145, no. 4 (July 28, 2016): 044106. http://dx.doi.org/10.1063/1.4958952.

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Hršak, Dalibor, Jógvan Magnus Haugaard Olsen, and Jacob Kongsted. "Polarizable Density Embedding Coupled Cluster Method." Journal of Chemical Theory and Computation 14, no. 3 (February 14, 2018): 1351–60. http://dx.doi.org/10.1021/acs.jctc.7b01153.

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Hedegård, Erik D., and Markus Reiher. "Polarizable Embedding Density Matrix Renormalization Group." Journal of Chemical Theory and Computation 12, no. 9 (September 2016): 4242–53. http://dx.doi.org/10.1021/acs.jctc.6b00476.

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Iannuzzi, Marcella, Barbara Kirchner, and Jürg Hutter. "Density functional embedding for molecular systems." Chemical Physics Letters 421, no. 1-3 (April 2006): 16–20. http://dx.doi.org/10.1016/j.cplett.2005.08.155.

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Niffenegger, K., Y. Oueis, J. Nafziger, and A. Wasserman. "Density embedding with constrained chemical potential." Molecular Physics 117, no. 15-16 (May 21, 2019): 2188–94. http://dx.doi.org/10.1080/00268976.2019.1618939.

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Dissertations / Theses on the topic "Density embedding"

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Wang, Haolei. "Using density-based clustering to improve skeleton embedding in the Pinocchio automatic rigging system." Thesis, Kansas State University, 2012. http://hdl.handle.net/2097/15102.

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Master of Science
Department of Computing and Information Sciences
William H. Hsu
Automatic rigging is a targeting approach that takes a 3-D character mesh and an adapted skeleton and automatically embeds it into the mesh. Automating the embedding step provides a savings over traditional character rigging approaches, which require manual guidance, at the cost of occasional errors in recognizing parts of the mesh and aligning bones of the skeleton with it. In this thesis, I examine the problem of reducing such errors in an auto-rigging system and apply a density-based clustering algorithm to correct errors in a particular system, Pinocchio (Baran & Popovic, 2007). I show how the density-based clustering algorithm DBSCAN (Ester et al., 1996) is able to filter out some impossible vertices to correct errors at character extremities (hair, hands, and feet) and those resulting from clothing that hides extremities such as legs.
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Reinhard, Teresa Elisabeth [Verfasser], and Angel [Akademischer Betreuer] Rubio. "Density Matrix Embedding Theory : Foundations, Applications and Connection to Functional Theories / Teresa Elisabeth Reinhard ; Betreuer: Angel Rubio." Hamburg : Staats- und Universitätsbibliothek Hamburg, 2019. http://d-nb.info/1186891157/34.

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Heuser, Johannes [Verfasser], and S. [Akademischer Betreuer] Höfener. "Analytische Kerngradienten für Frozen-Density Embedding-RICC2 zur Untersuchung angeregter Zustände komplexer Systeme / Johannes Heuser ; Betreuer: S. Höfener." Karlsruhe : KIT-Bibliothek, 2018. http://d-nb.info/1168325676/34.

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Mordovina, Uliana [Verfasser], and Angel [Akademischer Betreuer] Rubio. "Novel Approaches in Quantum Chemistry : Self-Consistent Density-Functional Embedding and Polaritonic Coupled-Cluster Theory / Uliana Mordovina ; Betreuer: Angel Rubio." Hamburg : Staats- und Universitätsbibliothek Hamburg, 2020. http://d-nb.info/1210647176/34.

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Senjean, Bruno. "Development of new embedding techniques for strongly correlated electrons : from in-principle-exact formulations to practical approximations." Thesis, Strasbourg, 2018. http://www.theses.fr/2018STRAF035/document.

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Cette thèse traite du développement et de l’implémentation de nouvelles méthodes visant à décrire la corrélation électronique forte dans les molécules et les solides. Après avoir introduit l’état de l’art des méthodes utilisées en chimie quantique et en physique de la matière condensée, une nouvelle méthode hybride combinant théorie de la fonction d’onde et théorie de la fonctionnelle de la densité (DFT) est présentée et s’intitule “site-occupation embedding theory” (SOET). Celle-ci est appliquée au modèle de Hubbard à une dimension. Ensuite, le problème du gap fondamental est revisité en DFT pour les ensembles, où la dérivée discontinue est réécrite comme une fonctionnelle de la densité de l'état fondamental. Enfin, une extension à la chimie quantique est proposée, basée sur une fonction d’onde de séniorité zéro complémentée par une fonctionnelle de la matrice densité, et exprimée dans la base des orbitales naturelles
The thesis deals with the development and implementation of new methods for the description of strong electron correlation effects in molecules and solids. After introducing the state of the art in quantum chemistry and in condensed matter physics, a new hybrid method so-called ``site-occupation embedding theory'' (SOET) is presented and is based on the merging of wavefunction theory and density functional theory (DFT). Different formulations of this theory are described and applied to the one-dimensional Hubbard model. In addition, a novel ensemble density functional theory approach has been derived to extract the fundamental gap exactly. In the latter approach, the infamous derivative discontinuity is reformulated as a derivative of a weight-dependent exchange-correlation functional. Finally, a quantum chemical extension of SOET is proposed and based on a seniority-zero wavefunction, completed by a functional of the density matrix and expressed in the natural orbital basis
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Werner, Martin. "Low-Scaling Local and Fragment Self-Consistent Field Potentials in Molecular Systems." Doctoral thesis, Niedersächsische Staats- und Universitätsbibliothek Göttingen, 2017. http://hdl.handle.net/11858/00-1735-0000-002E-E311-5.

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Hayashi, Kazuki. "Reinforcement Learning for Optimal Design of Skeletal Structures." Doctoral thesis, Kyoto University, 2021. http://hdl.handle.net/2433/263614.

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Pritzsche, Marc. "Dichtefunktional-Rechnungen zu selektiven Oxidationen von Propan und Methanol mittels Vanadiumoxidkatalysatoren auf Siliziumdioxidträgern." Doctoral thesis, Humboldt-Universität zu Berlin, Mathematisch-Naturwissenschaftliche Fakultät I, 2008. http://dx.doi.org/10.18452/15832.

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In der vorliegenden Arbeit wurden Cluster- und QM/MM-Einbettungsmodelle für geträgerte Vanadiumoxidkatalysatoren auf Siliziumdioxid mit Hilfe von DFT-Rechnungen untersucht. Es wurden Strukturen, Schwingungen und die Stabilität gegenüber Wasser und Sauerstoff unter Reaktionsbedingungen betrachtet. Ferner wurde die Reaktivität bei der Oxidativen Dehydrierung (ODH) von n-Propan zu n-Propen und der Oxidation von Methanol zu Formaldehyd untersucht. Zur Durchführung der Einbettungsrechnung wurde ein angepasstes Shell-Model-Potential verwendet. Bezüglich der Schwingungen zeigte sich, dass sich der Einfluss der Einbettung hauptsächlich auf die Kopplung von Schwingungen beschränkt, aber die Frequenzen kaum verändert werden. Die lokale Struktur um das Vanadiumatom beeinflusst die Vanadylschwingung wenig. Die Stabilitätsberechnungen haben gezeigt, dass die untersuchten Modelle unter Reaktionsbedingungen vorliegen und hydroxylierte Spezies keine Bedeutung haben. Bei der Untersuchung der beiden Reaktionen wird für die Cluster- und die QM/MM-Einbettungsrechnungen jeweils derselbe Mechanismus gefunden. Der Vorteil der Einbettungsrechnungen besteht darin, dass die lokale Struktur um das aktive Zentrum variiert werden kann. Bei der ODH von Propan hat die lokale Struktur einen eher geringen Einfluss auf die Reaktionsenergien, denn die Reaktion verläuft hauptsächlich am Vanadylsauerstoff. Der Übergangszustand des geschwindigkeitsbestimmenden Schrittes liegt bei der Einbettungsrechnung dennoch energetisch höher. Grund ist eine sterische Hinderung durch die Hydroxylgruppen der Oberfläche. Bei der Oxidation von Methanol ist der Einfluss der lokalen Struktur größer, denn die Reaktion verläuft sowohl über den Vanadylsauerstoff als auch über die Brückensauerstoffatome zum Trägermaterial. Für beide Reaktionen wird ein Einfluss der Vanadiumbeladung auf die Reaktionsenergien gefunden. Bei höherer Beladung werden die Reaktionen exothermer.
In this work cluster models and models for QM/MM-embedding for supported vanadia catalysts on silica were studied with help of DFT-calculations. The structures, vibrations and stability towards water and oxygen under reaction conditions were examined. Furthermore the reactivities towards the oxidative dehydrogenation (ODH) of n-propane to n-propene and the oxidation of methanol to formaldehyde were tested. For the embedding an adapted shell-model-potential was employed. Regarding the vibrations it was shown that the influence of the embedding lies mostly in the coupling of vibrations and not in their frequencies. The local structure surrounding the vanadium atom has only minor influence. The stability calculations have shown that the tested model systems exist under reaction conditions while hydroxylated species do not exist. When studying the reactivity of the two reactions always the same mechanism is found for cluster and embedded calculations. The benefit of the embedded calculations is the possibility to vary the local structure surrounding the active center. For the ODH of propane the local structure has only small impact on reaction energies because the reaction takes mainly place at the vanadyl oxygen. The transition state of the rate determining step nevertheless is energetically higher in the embedded calculations due to steric hindrance caused by the hydroxyl groups of the surface. The impact of local structure is more important for the oxidation of methanol since in this case vanadyl oxygen and bridging oxygens to the support are involved in the reaction. For both reactions an influence on reaction energies of the vanadia loading is found. With more loading the reactions becomes more exothermic.
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Goodpaster, Jason Daniel. "Density Functional Theory Embedding for Correlated Wavefunctions." Thesis, 2014. https://thesis.library.caltech.edu/8451/2/thesis_goodpaster.pdf.

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Methods that exploit the intrinsic locality of molecular interactions show significant promise in making tractable the electronic structure calculation of large-scale systems. In particular, embedded density functional theory (e-DFT) offers a formally exact approach to electronic structure calculations in which the interactions between subsystems are evaluated in terms of their electronic density. In the following dissertation, methodological advances of embedded density functional theory are described, numerically tested, and applied to real chemical systems.

First, we describe an e-DFT protocol in which the non-additive kinetic energy component of the embedding potential is treated exactly. Then, we present a general implementation of the exact calculation of the non-additive kinetic potential (NAKP) and apply it to molecular systems. We demonstrate that the implementation using the exact NAKP is in excellent agreement with reference Kohn-Sham calculations, whereas the approximate functionals lead to qualitative failures in the calculated energies and equilibrium structures.

Next, we introduce density-embedding techniques to enable the accurate and stable calculation of correlated wavefunction (CW) in complex environments. Embedding potentials calculated using e-DFT introduce the effect of the environment on a subsystem for CW calculations (WFT-in-DFT). We demonstrate that WFT-in-DFT calculations are in good agreement with CW calculations performed on the full complex.

We significantly improve the numerics of the algorithm by enforcing orthogonality between subsystems by introduction of a projection operator. Utilizing the projection-based embedding scheme, we rigorously analyze the sources of error in quantum embedding calculations in which an active subsystem is treated using CWs, and the remainder using density functional theory. We show that the embedding potential felt by the electrons in the active subsystem makes only a small contribution to the error of the method, whereas the error in the nonadditive exchange-correlation energy dominates. We develop an algorithm which corrects this term and demonstrate the accuracy of this corrected embedding scheme.

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Chen, Kai-Ren, and 陳楷壬. "A study of an efficient embedding algorithm for low-density generator matrix embedding." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/33405377748998150451.

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碩士
國立勤益科技大學
資訊工程系
102
This study investigated the belief propagation(Bias Propagation, BiP) algorithm proposed by Fridrich. Low-density parity-check [9] (LDPC) coding is a matrix embedding method. If a parity-check matrix with LDPC codes serves as a generator matrix and the BiP [1] algorithm is derived from this coding framework, the embedding efficiency and the computation speed of the BiP algorithm are superior to that of conventional matrix algorithms. In this study, MATLAB was used to simulate experimental data obtained from various algorithms. The results indicated that the embedding efficiency of the BiP algorithm surpassed that of other previously investigated algorithms. For the BiP algorithm, four parameters (i.e., gamma, iteration, damping, and generator matrix G) most easily affect the embedding efficiency of the algorithm. Furthermore, the method proposed by Richardson was used to design a new low-density generator matrix [2] (LDGM). Overall, simulations were performed to suboptimal parametric values, and possible combinations were simulated using LDGM with various embedding rates. The goal was to identify the optimal parametric values under various experimental data. In addition, regarding the BiP algorithm, a damping method that involves using arithmetic averages was proposed to reduce the computation complexity than that of the original damping procedure.
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Books on the topic "Density embedding"

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Guhr, Thomas. Replica approach in random matrix theory. Edited by Gernot Akemann, Jinho Baik, and Philippe Di Francesco. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780198744191.013.8.

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This article examines the replica method in random matrix theory (RMT), with particular emphasis on recently discovered integrability of zero-dimensional replica field theories. It first provides an overview of both fermionic and bosonic versions of the replica limit, along with its trickery, before discussing early heuristic treatments of zero-dimensional replica field theories, with the goal of advocating an exact approach to replicas. The latter is presented in two elaborations: by viewing the β = 2 replica partition function as the Toda lattice and by embedding the replica partition function into a more general theory of τ functions. The density of eigenvalues in the Gaussian Unitary Ensemble (GUE) and the saddle point approach to replica field theories are also considered. The article concludes by describing an integrable theory of replicas that offers an alternative way of treating replica partition functions.
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Book chapters on the topic "Density embedding"

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Wouters, Sebastian, Carlos A. Jiménez-Hoyos, and Garnet K.L. Chan. "Five Years of Density Matrix Embedding Theory." In Fragmentation, 227–43. Chichester, UK: John Wiley & Sons, Ltd, 2017. http://dx.doi.org/10.1002/9781119129271.ch8.

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Yu, Kuang, Caroline M. Krauter, Johannes M. Dieterich, and Emily A. Carter. "Density and Potential Functional Embedding: Theory and Practice." In Fragmentation, 81–117. Chichester, UK: John Wiley & Sons, Ltd, 2017. http://dx.doi.org/10.1002/9781119129271.ch2.

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Barbaglia, Luca, Sergio Consoli, and Sebastiano Manzan. "Exploring the Predictive Power of News and Neural Machine Learning Models for Economic Forecasting." In Mining Data for Financial Applications, 135–49. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-66981-2_11.

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AbstractForecasting economic and financial variables is a challenging task for several reasons, such as the low signal-to-noise ratio, regime changes, and the effect of volatility among others. A recent trend is to extract information from news as an additional source to forecast economic activity and financial variables. The goal is to evaluate if news can improve forecasts from standard methods that usually are not well-specified and have poor out-of-sample performance. In a currently on-going project, our goal is to combine a richer information set that includes news with a state-of-the-art machine learning model. In particular, we leverage on two recent advances in Data Science, specifically on Word Embedding and Deep Learning models, which have recently attracted extensive attention in many scientific fields. We believe that by combining the two methodologies, effective solutions can be built to improve the prediction accuracy for economic and financial time series. In this preliminary contribution, we provide an overview of the methodology under development and some initial empirical findings. The forecasting model is based on DeepAR, an auto-regressive probabilistic Recurrent Neural Network model, that is combined with GloVe Word Embeddings extracted from economic news. The target variable is the spread between the US 10-Year Treasury Constant Maturity and the 3-Month Treasury Constant Maturity (T10Y3M). The DeepAR model is trained on a large number of related GloVe Word Embedding time series, and employed to produce point and density forecasts.
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Wesolowski, Tomasz A. "Chapter 8. Hohenberg–Kohn Theorems as a basis for Multi-scale Simulations: Frozen-density Embedding Theory." In Theoretical and Computational Chemistry Series, 227–53. Cambridge: Royal Society of Chemistry, 2021. http://dx.doi.org/10.1039/9781839164668-00227.

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Das, Sourav, and Solomon Tesfamariam. "Reliability Based Design Optimization of Damped-Outrigger Timber Structure Using Stochastic Spectral Embedding Based Probability Density Evolution Method." In Lecture Notes in Civil Engineering, 273–84. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-21187-4_22.

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Fradelos, Georgios, Jesse J. Lutz, Tomasz A. Wesołowski, Piotr Piecuch, and Marta Włoch. "Shifts in Excitation Energies Induced by Hydrogen Bonding: A Comparison of the Embedding and Supermolecular Time-Dependent Density Functional Theory Calculations with the Equation-of-Motion Coupled-Cluster Results." In Advances in the Theory of Quantum Systems in Chemistry and Physics, 219–48. Dordrecht: Springer Netherlands, 2011. http://dx.doi.org/10.1007/978-94-007-2076-3_13.

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Thebaud, Thomas, Gaël Le Lan, and Anthony Larcher. "Unsupervised Labelling of Stolen Handwritten Digit Embeddings with Density Matching." In Lecture Notes in Computer Science, 545–63. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-61638-0_30.

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Lee, Junghyuk, and Jong-Seok Lee. "TREND: Truncated Generalized Normal Density Estimation of Inception Embeddings for GAN Evaluation." In Lecture Notes in Computer Science, 87–103. Cham: Springer Nature Switzerland, 2022. http://dx.doi.org/10.1007/978-3-031-20050-2_6.

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Neugebauer, Johannes. "Orbital-Free Embedding Calculations of Electronic Spectra." In Recent Progress in Orbital-free Density Functional Theory, 323–54. WORLD SCIENTIFIC, 2013. http://dx.doi.org/10.1142/9789814436731_0011.

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Gritsenko, O. V. "On the Principal Difference Between the Exact and Approximate Frozen-Density Embedding Theory." In Recent Progress in Orbital-free Density Functional Theory, 355–65. WORLD SCIENTIFIC, 2013. http://dx.doi.org/10.1142/9789814436731_0012.

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Conference papers on the topic "Density embedding"

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Zhou, Chunting, Xuezhe Ma, Di Wang, and Graham Neubig. "Density Matching for Bilingual Word Embedding." In Proceedings of the 2019 Conference of the North. Stroudsburg, PA, USA: Association for Computational Linguistics, 2019. http://dx.doi.org/10.18653/v1/n19-1161.

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Guo, Xueping, Xia Zhang, Jing Zhou, Liqiang Cao, and Lixi Wan. "Thermal management and characterization of the active component embedding into organic substrate." In High Density Packaging (ICEPT-HDP). IEEE, 2011. http://dx.doi.org/10.1109/icept.2011.6067033.

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Guo, Senhui, Jing Xu, Dapeng Chen, Chao Zhang, Xiaogang Wang, and Rui Zhao. "Density-Aware Feature Embedding for Face Clustering." In 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2020. http://dx.doi.org/10.1109/cvpr42600.2020.00673.

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Sawlani, Saurabh, Lingxiao Zhao, and Leman Akoglu. "Fast Attributed Graph Embedding via Density of States." In 2021 IEEE International Conference on Data Mining (ICDM). IEEE, 2021. http://dx.doi.org/10.1109/icdm51629.2021.00067.

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Sriperumbudur, Bharath K. "Mixture density estimation via Hilbert space embedding of measures." In 2011 IEEE International Symposium on Information Theory - ISIT. IEEE, 2011. http://dx.doi.org/10.1109/isit.2011.6033685.

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Xu, Pinghua, Yibing Zhan, Liu Liu, Baosheng Yu, Bo Du, Jia Wu, and Wenbin Hu. "Dual-branch Density Ratio Estimation for Signed Network Embedding." In WWW '22: The ACM Web Conference 2022. New York, NY, USA: ACM, 2022. http://dx.doi.org/10.1145/3485447.3512171.

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Xu, Pinghua, Yibing Zhan, Liu Liu, Baosheng Yu, Bo Du, Jia Wu, and Wenbin Hu. "Dual-branch Density Ratio Estimation for Signed Network Embedding." In WWW '22: The ACM Web Conference 2022. New York, NY, USA: ACM, 2022. http://dx.doi.org/10.1145/3485447.3512171.

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Bustos-Brinez, Oscar, Joseph Gallego, and Fabio Gonzalez. "Anomaly Detection through Density Matrices and Kernel Density Estimation (AD-DMKDE)." In LatinX in AI at Neural Information Processing Systems Conference 2022. Journal of LatinX in AI Research, 2022. http://dx.doi.org/10.52591/lxai2022112810.

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This paper presents a novel anomaly detection method, called AD-DMKDE, based on the use of Kernel Density Estimation (KDE) along with density matrices (a powerful mathematical formalism from quantum mechanics) and Fourier features. The proposed method was systematically compared with eleven state-of-the-art anomaly detection methods on various data sets, and AD-DMKDE shows competitive performance. The method uses neural-network optimization to find the parameters of data embedding, and the prediction phase complexity of the proposed algorithm is constant relative to the training data size.
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Wang, Baoyan, Jian Zhang, Fanggui Ding, and Yuexian Zou. "Multi-document news summarization via paragraph embedding and density peak clustering." In 2017 International Conference on Asian Language Processing (IALP). IEEE, 2017. http://dx.doi.org/10.1109/ialp.2017.8300593.

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Zhou, Yang, Amnay Amimeur, Chao Jiang, Dejing Dou, Ruoming Jin, and Pengwei Wang. "Density-aware Local Siamese Autoencoder Network Embedding with Autoencoder Graph Clustering." In 2018 IEEE International Conference on Big Data (Big Data). IEEE, 2018. http://dx.doi.org/10.1109/bigdata.2018.8621992.

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Reports on the topic "Density embedding"

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Chen, Jiankun, Yingming Gu, Lihong Yin, Minyi He, Na Liu, Yue Lu, Changcai Xie, Jiqiang Li, and Yu Chen. Network meta-analysis of curative efficacy of different acupuncture methods on obesity combined with insulin resistance. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, August 2022. http://dx.doi.org/10.37766/inplasy2022.8.0075.

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Review question / Objective: Population：Patients diagnosed as obesity with insulin resistance. Obesity reference: Consensus of experts on the Prevention and treatment of adult obesity in China in 2011 and Consensus of Chinese experts on medical nutrition therapy for overweight/obesity in 2016 were developed by the Obesity Group of Chinese Society of Endocrinology(CSE); BMI≥28. IR reference: According to the Expert opinions on insulin resistance evaluation published by Chinese Diabetes Society, HOMA-IR≥2.68 is regarded as the standard for the diagnosis of IR. Regardless of age, gender and course of disease. Patients diagnosed as obesity with insulin resistance. Intervention：Any kind of acupuncture, moxibustion, acupuncture+moxibustion, warm acupuncture, electropuncture, auricular point, acupoint application and acupoint catgut embedding. Comparison：Other acupuncture treatments, Drug therapy or blank control. Outcome：Primary outcomes: ①Fasting blood-glucose (FBG); ②Fasting serum insulin (FINS); ③Homeostasis model assessment-IR (HOMA-IR); ④Body Mass Index (BMI). Secondary outcomes: ①Waistline; ②Waist-hip ratio;③Triglyceride (TG); ④Total cholesterol (TC); ⑤High-density lipoprotein (HDL); ⑥Low-density lipoprotein (LDL). Study: Randomized controlled trials (RCTs) of different acupuncture methods in the treatment on obesity with insulin resistance, blind method and language are not limited. Randomized controlled trials (RCTs).
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