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Higher derivatives driven symmetry breaking in holographic superconductors

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arXiv 2019年

作者： Li, Hai-Li Fu, Guoyang Liu, Yan Wu, Jian-Pin Zhang, Xin Department of Physics College of Sciences Northeastern University Shenyang110819 China Center for Gravitation and Cosmology College of Physical Science and Technology Yangzhou University Yangzhou225009 China School of Aeronautics and Astronautics Shanghai Jiao Tong University Shanghai200240 China Ministry of Education’s Key Laboratory of Data Analytics and Optimization for Smart Industry Northeastern University Shenyang110819 China Center for High Energy Physics Peking University Beijing100080 China

In this paper, we construct a novel holographic superconductor from higher derivative (HD) gravity involving a coupling between the complex scalar field and the Weyl tensor. This HD coupling term provides a near horizon effective mass squared, which can violates IR Breitenlohner-Freedman (BF) bound by tuning the HD coupling and induces the instability of black brane such that the superconducting phase transition happens. We also study the properties of the condensation and the conductivity in the probe limit. We find that a wider extension of the superconducting energy gap ranging from 4.6 to 10.5 may provide a novel platform to model and interpret the phenomena in the real materials of high temperature superconductor. Copyright © 2019, The Authors. All rights reserved.

关键词： High temperature superconductors

Dynamic radiomics: A new methodology to extract quantitative time-related features from tomographic images

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arXiv 2020年

作者： Che, Fengying Shi, Ruichuan Li, Shuqin Wu, Jian Li, Haoran Chen, Weixing Zhang, Hao Qu, Hui Li, Zhi Cui, Xiaoyu College of Medicine and Biological Information Engineering Northeastern University Liaoning Shenyang China Key Laboratory of Intelligent Computing in Medical Image Ministry of Education Key Laboratory of Data Analytics and Optimization for Smart Industry Northeastern University Liaoning Shenyang China Department of Medical Oncology The First Affiliated Hospital of China Medical University Liaoning110001 China Shenzhen College of Advanced Technology University of the Chinese Academy of Sciences Beijing100049 China Department of Breast Surgery Liaoning Cancer Hospital and Institute Cancer Hospital of China Medical University Liaoning Shenyang110042 China

The feature extraction methods of radiomics are mainly based on static tomographic images at a certain moment, while the occurrence and development of disease is a dynamic process that cannot be fully reflected by only static characteristics. This study proposes a new dynamic radiomics feature extraction workflow that uses time-dependent tomographic images of the same patient, focuses on the changes in image features over time, and then quantifies them as new dynamic features for diagnostic or prognostic evaluation. We first define the mathematical paradigm of dynamic radiomics and introduce three specific methods that can describe the transformation process of features over time. Three different clinical problems are used to validate the performance of the proposed dynamic feature with conventional 2D and 3D static *** results show that compared with static features, dynamic feature extraction can achieve higher robustness and accuracy for time-dependent tomographic images. We also found that the dynamic features that influence different clinical problems are also quite different. Copyright © 2020, The Authors. All rights reserved.

关键词： Tomography

Publisher Correction: Two-stage salient object detection based on prior distribution learning and saliency consistency optimization

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The Visual Computer 2022年第12期39卷 6771-6771页

作者： Wu, Yunhe Chang, Xingya Chen, Dongyue Chen, Lei Jia, Tong College of Information Science and Engineering Northeastern University Shenyang China Midea Group Shanghai China Key Laboratory of Data Analytics and Optimization for Smart Industry Northeastern University Ministry of Education Shenyang China

optimization of the raw material field layout for iron-steel enterprise

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IOP Conference Series: Materials Science and Engineering 2019年第2期631卷

作者： Wenbo Liu Yuehong Kong Department of Logistics Management Liaoning Provincial College of Communications Shenyang Liaoning 110122 China. Key Laboratory of Data Analytics and Optimization for Smart Industry (Northeastern University) Shenyang Liaoning 110819 China.

This paper studies a short-term layout optimization problem with the raw material field for iron-steel enterprises. The raw material field is a centralized storage place and distribution unit of various raw materials such as iron ore, which plays a significant role in the iron front logistics for iron and steel enterprises. Whether the stacking of raw materials is reasonable or not directly affects the logistics efficiency and logistics cost of raw materials for iron-steel enterprises. Based on the status and basic information of the raw materials, storage space of the field shall be made full use of to allocate the optimal position for each type of raw material. To achieve this goal, a mixed integer programming (MIP) model is developed, which is purposed to minimize the transportation cost and the loss of mixing. The solution compares favorably with the current practice in the iron-steel enterprises.

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Theoretical Study on Coal Gasification Behavior in CO2 Atmosphere Driven by Slag Waste Heat

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SSRN

SSRN 2023年

作者： Duan, Wenjun Yang, Shuo Han, Jiachen Wu, Qinting Li, Peishi Cheng, Peiwen Lv, Xiaojun Wang, Zhimei Yu, Qingbo School of Metallurgy Northeastern University No 11 Lane 3 Wenhua Road Heping District Liaoning Shenyang110819 China College of Energy and Environment Shenyang Aerospace University No. 37 Daoyi South Street Shenbei New District Liaoning Shenyang110136 China National Frontiers Science Center for Industrial Intelligence and Systems Optimization Northeastern University No. 11 Lane 3 Wenhua Road Heping District Liaoning Shenyang110819 China Key Laboratory of Data Analytics and Optimization for Smart Industry Northeastern University Ministry of Education No. 11 Lane 3 Wenhua Road Heping District Liaoning Shenyang110819 China Northeastern University United States

Blast furnace slag, a main by-product of ironmaking process, contained high-quality sensible heat, accounting for almost 30% of total energy consumption in iron and steel industry. This paper proposed CO2 coal gasification method aimed at recovering waste heat from blast furnace slag. Based on Gibbs free energy minimization, influence of temperature, CO2/C, pressure and steam were investigated. Under optimal operating conditions at 1023~1198 K, CO2/C of 1.5~2.0 and atmospheric pressure, total amount of syngas was 2.78 kmol, with 67.1% CO and 8.79% H2. Addition of steam could adjust the compositions of syngas. H2/CO of syngas reached 1.0, 1.5 and 2.0 when H2O(g)/CO2 were 1.45/0.55, 1.73/0.27 and 1.95/0.05, which could be used as organic raw materials for chemical industry. Meantime, energy and exergy analysis were utilized to comprehend energy utilization effect of gasification reaction process. Energy and exergy efficiency of coal gasification were found to be 92.76% and 86.26%, respectively, under optimal operation conditions. For different syngas products, when H2O(g)/CO2 was 1.95/0.05, exergy loss was the lowest, with internal and external exergy loss amounting to 10.27% and 0.99% respectively. Utilizing coal gasification reaction was important for recovery of waste heat from blast furnace slag and reduction of CO2 emissions. © 2023, The Authors. All rights reserved.

关键词： Waste heat

The Three Hundred Project: The relationship between the shock and splashback radii of simulated galaxy clusters

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arXiv 2024年

作者： Zhang, M. Walker, K. Sullivan, A. Power, C. Cui, W. Li, Y. Zhang, X. College of Sciences Northeastern University Shenyang110819 China International Centre for Radio Astronomy Research The University of Western Australia 35 Stirling Highway CrawleyWA6009 Australia Australia Departamento de Física Teórica Módulo 15 Facultad de Ciencias Universidad Autónoma de Madrid Madrid28049 Spain Universidad Autónoma de Madrid Cantoblanco MadridE-28049 Spain Key Laboratory of Data Analytics and Optimization for Smart Industry Ministry of Education Northeastern University Shenyang110819 China National Frontiers Science Center for Industrial Intelligence and Systems Optimization Northeastern University Shenyang110819 China

Observations of the intracluster medium (ICM) in the outskirts of galaxy clusters reveal shocks associated with gas accretion from the cosmic web. Previous work based on non-radiative cosmological hydrodynamical simulations have defined the shock radius, rshock, using the ICM entropy, K ∝ T/ne2/3, where T and ne are the ICM temperature and electron density respectively;the rshock is identified with either the radius at which K is a maximum or at which its logarithmic slope is a minimum. We investigate the relationship between rshock, which is driven by gravitational hydrodynamics and shocks, and the splashback radius, rsplash, which is driven by the gravitational dynamics of cluster stars and dark matter and is measured from their mass profile. Using 324 clusters from The Three Hundred project of cosmological galaxy formation simulations, we quantify statistically how rshock relates to rsplash. Depending on our definition, we find that the median rshock 1.38rsplash(2.58R200) when K reaches its maximum and rshock 1.91rsplash(3.54R200) when its logarithmic slope is a minimum;the best-fit linear relation increases as rshock ∝ 0.65rsplash. We find that rshock/R200 and rsplash/R200 anti-correlate with virial mass, M200, and recent mass accretion history, and rshock/rsplash tends to be larger for clusters with higher recent accretion rates. We discuss prospects for measuring rshock observationally and how the relationship between rshock and rsplash can be used to improve constraints from radio, X-ray, and thermal Sunyaev-Zeldovich surveys that target the interface between the cosmic web and clusters. Copyright © 2024, The Authors. All rights reserved.

关键词： Dark Matter

Ammonium-Ion Storage Using Electrodeposited Manganese Oxides

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Angewandte Chemie 2020年第11期133卷

作者： Dr. Yu Song Qing Pan Huizhen Lv Duo Yang Zengming Qin Ming-Yue Zhang Prof. Xiaoqi Sun Prof. Xiao-Xia Liu Department of Chemistry Northeastern University 3-11 Wenhua Road Heping district Shenyang 110819 China Key Laboratory of Data Analytics and Optimization for Smart Industry Northeastern University 3-11 Wenhua Road Heping district Shenyang 110819 China

NH 4 + ions as charge carriers show potential for aqueous rechargeable batteries. Studied here for the first time is the NH 4 + -storage chemistry using electrodeposited manganese oxide (MnO x ). MnO x experiences morphology and phase transformations during charge/discharge in dilute ammonium acetate (NH 4 Ac) electrolyte. The NH 4 Ac concentration plays an important role in NH 4 + storage for MnO x . The transformed MnO x with a layered structure delivers a high specific capacity (176 mAh g −1 ) at a current density of 0.5 A g −1 , and exhibits good cycling stability over 10 000 cycles in 0.5 M NH 4 Ac, outperforming the state-of-the-art NH 4 + hosting materials. Experimental results suggest a solid-solution behavior associated with NH 4 + migration in layered MnO x . Spectroscopy studies and theoretical calculations show that the reversible NH 4 + insertion/deinsertion is accompanied by hydrogen-bond formation/breaking between NH 4 + and the MnO x layers. These findings provide a new prototype (i.e., layered MnO x ) for NH 4 + -based energy storage and contributes to the fundamental understanding of the NH 4 + -storage mechanism for metal oxides.

关键词： batteries energy storage hydrogen bonding manganese phase transformations

Dark energy and matter interacting scenario to relieve H0 and S8 tensions

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arXiv 2022年

作者： Gao, Li-Yang Xue, She-Sheng Zhang, Xin Department of Physics College of Sciences Northeastern University Shenyang110819 China Kapteyn Astronomical Institute University of Groningen P.O. Box 800 Groningen9700 AV Netherlands ICRANet Piazzale della Repubblica Pescara10-65122 Italy ICTP-AP University of Chinese Academy of Sciences Beijing China Physics Department Sapienza University of Rome P.le A. Moro 5 Rome00185 Italy INFN Sezione di Perugia Via A. Pascoli PerugiaI-06123 Italy Key Laboratory of Data Analytics and Optimization for Smart Industry Ministry of Education Northeastern University Shenyang110819 China National Frontiers Science Center for Industrial Intelligence and Systems Optimization Northeastern University Shenyang110819 China

We consider a new cosmological model (called Λ˜CDM) in which the vacuum energy interacts with matter and radiation, and test this model using the current cosmological observations. Using the CMB+BAO+SN (CBS) dataset to constrain the model, we find that H0 and S8 tensions are relieved to 2.87σ and 2.77σ, respectively. However, in this case, the Λ˜CDM model is not favored by the data, compared with ΛCDM. We find that when the H0 and S8 data are added to the data combination, the situation is significantly improved. In the CBS+H0 case, the model relieves the H0 tension to 0.47σ, and the model is favored over ΛCDM. In the CBS+H0+S8 case, we obtain a synthetically best situation, in which the H0 and S8 tensions are relieved to 0.72σ and 2.11σ, respectively. In this case, the model is most favored by the data. Therefore, this cosmological model can greatly relieve the H0 tension and simultaneously effectively alleviate the S8 tension. Copyright © 2022, The Authors. All rights reserved.

关键词： Electric circuit breakers

Intention-sensitive Preference Learning Network for Personalized Session-based Recommendation

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ACM Transactions on Recommender Systems 1000年

作者： Qingbo Zhang Xiaochun Yang Hao Chen Bin Wang Xiangmin Zhou Computer Science and Engineering Northeastern University Shenyang China Northeastern University Shenyang China National Frontiers Science Center for Industrial Intelligence and Systems Optimization Shenyang China Key Laboratory of Data Analytics and Optimization for Smart Industry Northeastern University Ministry of Education Shenyang China School of Computing Technologies RMIT University Melbourne Australia

Nowadays, research on session-based recommender systems (SRSs) is one of the hot spots in the recommendation domain. Existing methods make recommendations based on the user’s current intention (also called short-term preference) during a session, often overlooking the specific preferences associated with these intentions. In reality, users usually exhibit diverse preferences for different intentions, and even for the same intention, individual preferences can vary significantly between users. As users interact with items throughout a session, their intentions can shift accordingly. To enhance recommendation quality, it is crucial not only to consider the user’s intentions but also to dynamically learn their varying preferences as these intentions change. In this paper, we propose a novel Intention-sensitive Preference Learning Network (IPLN) including three main modules: intention recognizer, preference detector, and prediction layer. Specifically, the intention recognizer infers the user’s underlying intention within his/her current session by analyzing complex relationships among items. Based on the acquired intention, the preference detector learns the intention-specific preference by selectively integrating latent features from items in the user’s historical sessions. Besides, the user’s general preference is utilized to refine the obtained preference to reduce the potential noise carried from historical records. Ultimately, the fine-tuned preference and intention collaborate to instruct the next-item recommendation in the prediction layer. To prove the effectiveness of the proposed IPLN, we perform extensive experiments on two real-world datasets. The experiment results demonstrate the superiority of IPLN compared with other state-of-the-art models.

关键词： session-based recommender systems personalized next-item recommendation user intention intention-specific preference