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Honeycomb-Lattice Mott Insulator on Tantalum Disulphide

Physical Review Letters 2020年第9期125卷 096403-096403页

作者： Jinwon Lee Kyung-Hwan Jin Andrei Catuneanu Ara Go Jiwon Jung Choongjae Won Sang-Wook Cheong Jaeyoung Kim Feng Liu Hae-Young Kee Han Woong Yeom Center for Artificial Low Dimensional Electronic Systems Institute for Basic Science (IBS) Pohang 37673 Republic of Korea Department of Physics Pohang University of Science and Technology Pohang 37673 Republic of Korea Department of Materials Science and Engineering University of Utah Salt Lake City Utah 84112 United States Department of Physics University of Toronto Ontario M5S 1A7 Canada Center for Theoretical Physics of Complex Systems Institute for Basic Science (IBS) Daejeon 34126 Republic of Korea Laboratory for Pohang Emergent Materials Pohang University of Science and Technology Pohang 37673 Republic of Korea Rutgers Center for Emergent Materials and Department of Physics and Astronomy Rutgers University Piscataway New Jersey 08854 United States Canadian Institute for Advanced Research CIFAR Program in Quantum Materials Toronto Ontario M5G 1M1 Canada

Effects of electron many-body interactions amplify in an electronic system with a narrow bandwidth opening a way to exotic physics. A narrow band in a two-dimensional (2D) honeycomb lattice is particularly intriguing as combined with Dirac bands and topological properties but the material realization of a strongly interacting honeycomb lattice described by the Kane-Mele-Hubbard model has not been identified. Here we report a novel approach to realize a 2D honeycomb-lattice narrow-band system with strongly interacting 5d electrons. We engineer a well-known triangular lattice 2D Mott insulator 1T−TaS2 into a honeycomb lattice utilizing an adsorbate superstructure. Potassium (K) adatoms at an optimum coverage deplete one-third of the unpaired d electrons and the remaining electrons form a honeycomb lattice with a very small hopping. Ab initio calculations show extremely narrow Z2 topological bands mimicking the Kane-Mele model. Electron spectroscopy detects an order of magnitude bigger charge gap confirming the substantial electron correlation as confirmed by dynamical mean field theory. It could be the first artificial Mott insulator with a finite spin Chern number.

关键词： Adsorption Topological materials Mott insulators Transition metal dichalcogenides Electron-correlation calculations Scanning tunneling microscopy

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Development of electric cart for improving walking ability — application of control theory to assistive technology

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Science China(Information Sciences) 2017年第12期60卷 262-270页

作者： Jinhua SHE Yasuhiro OHYAMA Min WU Hiroshi HASHIMOTO School of Engineering Tokyo University of Technology School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Master Program of Innovation for Design & Engineering Advanced Institute of Industrial Technology

This paper explains the development of an electric cart that helps the elderly maintain or improve their physical strength. Unlike commercially available ones, it has a pedal unit that provides some exercise for a user in training his lower limbs. An impedance model describes the feeling of pushing the pedals. The largest pedal load is determined based on a pedaling experiment. An H∞ controller is designed for each of the largest pedal load and virtually no load. A control law, which is based on the concept of dynamic parallel distributed compensation, is designed using the rating of perceived exertion of a driver as a criterion to choose a pedal load between the largest and almost zero. Five university students and twelve elderly people participated experiments to verify the system design and the validity of the system.

关键词： aging Borg’s scale dynamic parallel distributed compensation electrical cart H_∞ control Karvonen formula lower limbs pedaling rating of perceived exertion

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Steady Rayleigh-BénardRayleigh-Bénard convection between stress-free boundaries

arXiv

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arXiv 2020年

作者： Wen, Baole Goluskin, David LeDuc, Matthew Chini, Gregory P. Doering, Charles R. Department of Mathematics University of Michigan Ann ArborMI48109-1043 United States Department of Mathematics & Statistics University of Victoria VictoriaBCV8P 5C2 Canada Department of Physics University of Michigan Ann ArborMI48109-1040 United States Program in Integrated Applied Mathematics University of New Hampshire DurhamNH03824 United States Department of Mechanical Engineering University of New Hampshire DurhamNH03824 United States Center for the Study of Complex Systems University of Michigan Ann ArborMI48109-1042 United States

Steady two-dimensional Rayleigh-Bénard convection between stress-free isothermal boundaries is studied via numerical computations. We explore properties of steady convective rolls with aspect ratios π/5 ⩽ Γ ⩽ 4π, where Γ is the width-to-height ratio for a pair of counter-rotating rolls, over eight orders of magnitude in the Rayleigh number, 103 ⩽ Ra ⩽ 1011, and four orders of magnitude in the Prandtl number, 10−2 ⩽ Pr ⩽ 102. At large Ra where steady rolls are dynamically unstable, the computed rolls display Ra → ∞ asymptotic scaling. In this regime, the Nusselt number Nu that measures heat transport scales as Ra1/3 uniformly in Pr. The prefactor of this scaling depends on Γ and is largest at Γ ≈ 1.9. The Reynolds number Re for large-Ra rolls scales as Pr−1Ra2/3 with a prefactor that is largest at Γ ≈ 4.5. All of these large-Ra features agree quantitatively with the semi-analytical asymptotic solutions constructed by Chini & Cox (2009). Convergence of Nu and Re to their asymptotic scalings occurs more slowly when Pr is larger and when Γ is smaller. Copyright © 2020, The Authors. All rights reserved.

关键词： Prandtl number

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Evaluation of an AI facial recognition system for Turner Syndrome screening and facial complexity: a prospective cohort

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International journal of medical informatics 2025年 203卷 105976页

作者： Jiaqi Qiang Weixin Hong Yuxin Sun Xiaohong Lyu Zhouxian Pan Danning Wu Zhibo Zhou Xiaoyuan Guo Hanze Du Hongbo Yang Huijuan Zhu Shi Chen Hui Pan Zhen Shen Key Laboratory of Endocrinology of National Health Commission Department of Endocrinology Peking Union Medical College Hospital Chinese Academy of Medical Sciences and Peking Union Medical College Beijing 100730 China. State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing 100190 China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing 100049 China. Key Laboratory of Endocrinology of National Health Commission Department of Endocrinology Peking Union Medical College Hospital Chinese Academy of Medical Sciences and Peking Union Medical College Beijing 100730 China Eight-Year Program of Clinical Medicine Chinese Academy of Medical Sciences and Peking Union Medical College Beijing 100730 China. Department of Breast Surgery Peking Union Medical College Hospital Chinese Academy of Medical Sciences and Peking Union Medical College Beijing 100730 China. Allergy Department Beijing Key Laboratory of Precision Medicine for Diagnosis and Treatment of Allergic Diseases National Clinical Research Center for Dermatologic and Immunologic Diseases Peking Union Medical College Hospital Chinese Academy of Medical Sciences and Peking Union Medical College Beijing 100730 China. Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing) Department of Radiation Oncology Peking University Cancer Hospital & Institute China. Key Laboratory of Endocrinology of National Health Commission Department of Endocrinology Peking Union Medical College Hospital Chinese Academy of Medical Sciences and Peking Union Medical College Beijing 100730 China. Electronic address: cs0083@***. State Key Laboratory of Complex Severe and Rare Diseases Peking Union Medical College Hospital Chinese Academy of Medical Sciences and Peking Union Medical College Beijing 100730 China. Electronic address: panhui20111111

PURPOSE:Artificial intelligence-based facial recognition (AI-FR) is promising in diagnosis of diseases with distinct facial features. Our team has retrospectively constructed an AI-FR system for Turner Syndrome (TS) based on 1295 facial photographs in previous research. This study aims to evaluate this AI-FR system for TS screening in a prospective cohort in real-world clinic setting. We also aim to elucidate the impact of complexity of facial features on diagnostic accuracy of AI-FR in this cohort. METHODS:Patients were recruited in a single-gate prospective cohort at a clinic. Facial images were collected for AI-FR diagnosis. Karyotype analyses were performed as the gold-standard diagnosis. Diagnostic performance of the AI-FR system was evaluated. Individual facial recognition intensity (iFRI) was proposed to characterize the complexity of individual facial features in patients. iFRI was calculated based on 26 facial landmarks of seven parts. Group comparison and regression analysis were performed on iFRI according to diagnosis classification. RESULTS:The prospective cohort included 218 patients (29 TS and 189 control). The AI-FR system showed performance: 89.0 % accuracy (95 % CI 84.1-92.5), 72.4 % sensitivity (95 % CI 54.3-85.3), and 91.5 % specificity (95 % CI 86.7-94.7). TS vs. control diagnosed by AI-FR had higher iFRI (p = 0.009), while TS vs. control diagnosed by gold standard showed no iFRI difference (p > 0.05). AI diagnosis classification positively correlated with iFRI (p = 0.033), while gold-standard classification did not (p > 0.05). CONCLUSION:This was one of the pioneering prospective cohorts in disease diagnosis with AI-FR. This system for TS screening achieved ideal performance and improved the diagnosis of TS. iFRI was proposed and proved influential to AI-FR diagnostic performance.

关键词： Artificial intelligence Diagnosis Machine learning Prospective cohort Turner Syndrome

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SAMENESS ENTICES, BUT NOVELTY ENCHANTS IN FANFICTION ONLINE

arXiv

引用

arXiv 2019年

作者： Jing, Elise DeDeo, Simon Wright, Devin Robert Ahn, Yong-Yeol Center for Complex Networks and Systems Research Luddy School of Informatics Computing and Engineering Indiana University Bloomington United States Social and Decision Sciences Dietrich College Carnegie Mellon University United States Sirius XM United States Cognitive Science Program Indiana University Bloomington United States Indiana University Network Science Institute Indiana University Bloomington United States

Cultural evolution is driven by how we choose what to consume and share with others. A common belief is that the cultural artifacts that succeed are ones that balance novelty and conventionality. This balance theory suggests that people prefer works that are familiar, but not so familiar as to be boring;novel, but not so novel as to violate the expectations of their genre. We test this idea using a large dataset of fanfiction. We apply a multiple regression model and a generalized additive model to examine how the recognition a work receives varies with its novelty, estimated through a Latent Dirichlet Allocation topic model, in the context of existing works. We find the opposite pattern of what the balance theory predicts—overall success decline almost monotonically with novelty and exhibits a U-shaped, instead of an inverse U-shaped, curve. This puzzle is resolved by teasing out two competing forces: sameness attracts the mass whereas novelty provides enjoyment. Taken together, even though the balance theory holds in terms of expressed enjoyment, the overall success can show the opposite pattern due to the dominant role of sameness to attract the audience. Under these two "forces", cultural evolution may have to work against inertia—the appetite for consuming the familiar—and may resemble a punctuated equilibrium, marked by occasional leaps. Copyright © 2019, The Authors. All rights reserved.

关键词： Large dataset

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Unifying femtosecond and picosecond single-pulse magnetic switching in GdFeCo

arXiv

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arXiv 2020年

作者： Jakobs, F. Ostler, T.A. Lambert, C.-H. Yang, Y. Salahuddin, S. Wilson, R.B. Gorchon, J. Bokor, J. Atxitia, U. Dahlem Center for Complex Quantum Systems and Fachbereich Physik Freie Universität Berlin Berlin14195 Germany LiégeB-4000 Belgium College of Business Technology and Engineering Sheffield Hallam University Howard Street SheffieldS1 1WB United Kingdom Department of Electrical Engineering and Computer Sciences University of California BerkeleyCA94720 United States Department of Materials Science and Engineering University of California BerkeleyCA94720 United States Lawrence Berkeley National Laboratory 1 Cyclotron Road BerkeleyCA94720 United States Department of Mechanical Engineering and Materials Science and Engineering Program University of California RiversideCA92521 United States ETH Zurich Hönggerbergring 64 Zürich8093 Switzerland Portland Technology Development Department Intel Corp. HillsboroOR97006 United States Universite de Lorraine CNRS IJL NancyF-54000 France

Many questions are still open regarding the physical mechanisms behind the magnetic switching in GdFeCo alloys by single optical pulses. Phenomenological models suggest a femtosecond scale exchange relaxation between sublattice magnetization as the driving mechanism for switching. The recent observation of thermally induced switching in GdFeCo by using both several picosecond optical laser pulse as well as electric current pulses has questioned this previous understanding. This has raised the question of whether or not the same switching mechanics are acting at the femoand picosecond scales. In this work, we aim at filling this gap in the understanding of the switching mechanisms behind thermal single-pulse switching. To that end, we have studied experimentally thermal single-pulse switching in GdFeCo alloys, for a wide range of system parameters, such as composition, laser power and pulse duration. We provide a quantitative description of the switching dynamics using atomistic spin dynamics methods with excellent agreement between the model and our experiments across a wide range of parameters and timescales, ranging from femtoseconds to picoseconds. Furthermore, we find distinct element-specific damping parameters as a key ingredient for switching with long picosecond pulses and argue, that switching with pulse durations as long as 15 picoseconds is possible due to a low damping constant of Gd. Our findings can be easily extended to speed up dynamics in other contexts where ferrimagnetic GdFeCo alloys have been already demonstrated to show fast and energy-efficient processes, e.g. domain-wall motion in a track and spin-orbit torque switching in spintronics devices. Copyright © 2020, The Authors. All rights reserved.

关键词： Ternary alloys

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Influence of autapses on synchronisation in neural networks with chemical synapses

arXiv

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arXiv 2020年

作者： Protachevicz, Paulo R. Iarosz, K.C. Caldas, I.L. Antonopoulos, C.G. Batista, A.M. Kurths, J. Institute of Physics University of São Paulo São Paulo SP Brazil Faculdade de Telêmaco Borba FATEB Telêmaco Borba Paraná Brazil Graduate Program in Chemical Engineering Federal University of Technology Paraná Ponta GrossaParaná Brazil Department of Mathematical Sciences University of Essex Wivenhoe Park United Kingdom Department of Mathematics and Statistics State University of Ponta Grossa Ponta Grossa PR Brazil Department Complexity Science Potsdam Institute for Climate Impact Research Potsdam Germany Department of Physics Humboldt University Berlin Germany Centre for Analysis of Complex Systems Sechenov First Moscow State Medical University Moscow Russia

A great deal of research has been devoted on the investigation of neural dynamics in various network topologies. However, only a few studies have focused on the influence of autapses, synapses from a neuron onto itself via closed loops, on neural synchronisation. Here, we build a random network with adaptive exponential integrate-and-fire neurons coupled with chemical synapses, equipped with autapses, to study the effect of the latter on synchronous behaviour. We consider time delay in the conductance of the pre-synaptic neuron for excitatory and inhibitory connections. Interestingly, in neural networks consisting of both excitatory and inhibitory neurons, we uncover that synchronous behaviour depends on their synapse type. Our results provide evidence on the synchronous and desynchronous activities that emerge in random neural networks with chemical, inhibitory and excitatory synapses where neurons are equipped with autapses. Copyright © 2020, The Authors. All rights reserved.

关键词： Synchronization

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Effects of drug resistance in the tumour-immune system with chemotherapy treatment

arXiv

引用

arXiv 2020年

作者： Trobia, José Gabrick, Enrique C. Seifert, Evandro G. Borges, Fernando S. Protachevicz, Paulo R. Szezech, José D. Iarosz, Kelly C. Santos, Moises S. Caldas, Iberê L. Tian, Kun Ren, Hai-Peng Grebogi, Celso Batista, Antonio M. Graduate Program in Science - Physics State University of Ponta Grossa Ponta GrossaPR84030-900 Brazil Department of Mathematics and Statistics State University of Ponta Grossa Ponta GrossaPR84030-900 Brazil Department of Physics State University of Ponta Grossa Ponta GrossaPR84030-900 Brazil Center for Mathematics Computation and Cognition Federal University of ABC São Bernardo do CampoSP09606-045 Brazil Institute of Physics University of São Paulo São PauloSP05508-900 Brazil Faculty of Telêmaco Borba FATEB Telêmaco BorbaPR84266-010 Brazil Graduate Program in Chemical Engineering Federal Technological University of Paraná Ponta Grossa Paraná84016-210 Brazil Shaanxi Key Lab of Complex System Control and Intelligent Information Processing Xi’an University of Technology Xi’an710048 China Xi’an Technological University Xi’an710021 China Institute for Complex Systems and Mathematical Biology University of Aberdeen AberdeenAB24 3UE United Kingdom

Cancer is a term used to refer to a large set of diseases. The cancerous cells grow and divide and, as a result, they form tumours that grow in size. The immune system recognise the cancerous cells and attack them, though, it can be weakened by the cancer. One type of cancer treatment is chemotherapy, which uses drugs to kill cancer cells. Clinical, experimental, and theoretical research has been developed to understand the dynamics of cancerous cells with chemotherapy treatment, as well as the interaction between tumour growth and immune system. We study a mathematical model that describes the cancer growth, immune system response, and chemotherapeutic agents. The immune system is composed of resting cells that are converted to hunting cells to combat the cancer. In this work, we consider drug sensitive and resistant cancer cells. We show that the tumour growth can be controlled not only by means of different chemotherapy protocols, but also by the immune system that attacks both sensitive and resistant cancer cells. Furthermore, for all considered protocols, we demonstrate that the time delay from resting to hunting cells plays a crucial role in the combat against cancer cells. Copyright © 2020, The Authors. All rights reserved.

关键词： Chemotherapy

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Influence of inhibitory synapses on the criticality of excitable neuronal networks

arXiv

引用

arXiv 2020年

作者： Borges, F.S. Protachevicz, P.R. Santos, V. Santos, M.S. Gabrick, E.C. Iarosz, K.C. Lameu, E.L. Baptista, M.S. Caldas, I.L. Batista, A.M. Center for Mathematics Computation and Cognition Federal University of ABC São Bernardo do CampoSP09606-045 Brazil Graduate Program in Science - Physics State University of Ponta Grossa Ponta Grossa PR84030-900 Brazil Institute of Physics University of São Paulo São PauloSP05508-900 Brazil Faculdade de Telêmaco Borba Telêmaco BorbaPR84266-010 Brazil Graduate Program in Chemical Engineering Federal University of Technology Paraná Ponta Grossa PR84016-210 Brazil Cell Biology and Anatomy Department University of Calgary AB T2N 4N1 CalgaryAB Canada Institute for Complex Systems and Mathematical Biology University of Aberdeen AberdeenScotlandAB24 3UE United Kingdom Department of Mathematics and Statistics State University of Ponta Grossa Ponta Grossa PR84030-900 Brazil

In this work, we study the dynamic range of a neuronal network of excitable neurons with excitatory and inhibitory synapses. We obtain an analytical expression for the critical point as a function of the excitatory and inhibitory synaptic intensities. We also determine an analytical expression that gives the critical point value in which the maximal dynamic range occurs. Depending on the mean connection degree and coupling weights, the critical points can exhibit ceasing or ceaseless dynamics. However, the dynamic range is equal in both cases. We observe that the external stimulus mask some effects of self-sustained activity (ceaseless dynamic) in the region where the dynamic range is calculated. In these regions, the firing rate is the same for ceaseless dynamics and ceasing activity. Furthermore, we verify that excitatory and inhibitory inputs are approximately equal for a network with a large number of connections, showing excitatory-inhibitory balance as reported experimentally. Copyright © 2020, The Authors. All rights reserved.

关键词： Dynamics

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Addendum: Discrepancy in scientific authority and media visibility of climate change scientists and contrarians

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Nature communications 2020年第1期11卷 553页

作者： Alexander Michael Petersen Emmanuel M Vincent Anthony LeRoy Westerling Management of Complex Systems Department Ernest and Julio Gallo Management Program School of Engineering University of California Merced CA 95343 USA. apetersen3@ucmerced.edu. Medialab Sciences Po 75007 Paris France. mel.manux@***. Center for Climate Communication University of California Merced CA 95343 USA. mel.manux@***. Management of Complex Systems Department Ernest and Julio Gallo Management Program School of Engineering University of California Merced CA 95343 USA. awesterling@ucmerced.edu. Center for Climate Communication University of California Merced CA 95343 USA. awesterling@ucmerced.edu. Sierra Nevada Research Institute University of California Merced CA 95343 USA. awesterling@ucmerced.edu.

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