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Lifshitz transition in triangular lattice Kondo-Heisenberg model

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Chinese Physics B 2020年第7期29卷 441-450页

作者： Lan Zhang yin Zhong Hong-gang Luo School of Physical Science and Technology&Key Laboratory for Magnetism and Magnetic Materials of Ministry of Education Lanzhou UniversityLanzhou 730000China Beijing Computational Science Research Center Beijing 100084China

Motivated by recent experimental progress on triangular lattice heavy-fermion compounds,we investigate possible Lifshitz transitions and the scanning tunnel microscope(STM)spectra of the Kondo-Heisenberg model on the triangular *** the heavy Fermi liquid state,the introduced Heisenberg antiferromagnetic interaction(JH)results in the twice Lifshitz transition at the case of the nearest-neighbour electron hopping but with next-nearest-neighbour hole hopping and the case of the nearest-neighbour hole hopping but with next-nearest-neighbour electron hopping,*** by JH,the Lifshitz transitions on triangular lattice are all continuous in contrast to the case on square ***,the STM spectra shows rich line-shape which is influenced by the Kondo coupling JK,the Heisenberg antiferromagnetic interaction JH,and the ratio of the tunneling amplitude of f-electron tf versus conduction electron *** work provides a possible scenario to understand the Fermi surface topology and the quantum critical point in heavy-fermion compounds.

关键词： Kondo-Heisenberg model Lifshitz transition heavy-fermion systems

Resistivity minimum emerges in Anderson impurity model modified with Sachdev-Ye-Kitaev interaction

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Chinese Physics B 2021年第4期30卷 465-474页

作者： Lan Zhang yin Zhong Hong-gang Luo School of Physical Science and Technology&Key Laboratory for Magnetism and Magnetic Materials of the Ministry of Education Lanzhou UniversityLanzhou 730000China Beijing Computational Science Research Center Beijing 100084China

We investigate a modified Anderson model at the large-N limit,where the Coulomb interaction is replaced by the Sachdev-Ye-Kitaev random *** resistivity of conduction electron ρ_(c) has a minimum value around temperature T^(*),which is similar to the Kondo system,but the impurity electron’s density of state A_(d)(ω) demonstrates no sharp-peak like the Kondo resonance around the Fermi *** provides a counterintuitive example where resistivity minimum exists without Kondo *** impurity electron’s entropy S_(d) and specific heat capacity C_(v) show a crossover from Fermi liquid to a non-Fermi liquid behavior dependent on *** system is a Fermi liquid at T T^(*),and then becomes a Fermi gas at sufficiently high temperatures T>>T^(*).The non-Fermi liquid at the intermediate-T regime does not occur in the standard Anderson *** also make a renormalization group analysis,which confirms the crossover from Fermi liquid to the non-Fermi *** is emphasized that the resistivity minimum emerges in our model when the system behaves as a non-Fermi liquid rather than Fermi liquid,which provides an alternative example showing resistivity minimum in condensed matter physics.

关键词： Anderson model Sachdev-Ye-Kitaev interaction non-Fermi liquid

Deep learning for electrolysis process anode effect prediction based on long short-term memory network and stacked denoising autoencoder

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Rare Metals 2024年第12期43卷 6730-6741页

作者： gang yin Yi-Hui Li Fei-Ya Yan peng-Cheng Quan Min Wang Wen-Qi Cao Heng-Quan Xu Jian Lu Wen He School of Resource and Safety Engineering and State Key Laboratory of Coal Mine Disaster Dynamics and Control Chongqing University Guiyang Aluminium Magnesium Design and Research Institute Co. Ltd. Aba Aluminium Factory Chongqing Qineng Electric Aluminium Co. Ltd. Bomei Qimingxing Aluminium Co. Ltd.

The anode effect is a common failure in the aluminium electrolysis *** the anode effect cannot be accurately predicted,it will cause increased energy consumption,harmful gas generation and even equipment damage in the aluminium *** this paper,an anode effect prediction framework using multi-model merging based on deep learning technology is *** models are used to process aluminium electrolysis cell condition parameters with high dimensions and different characteristics,and hidden key fault information is deeply mined.A stacked denoising autoencoder is utilized to denoise and extract features from a large number of longperiod parameter data.A long short-term memory network is implemented to identify the intrinsic links between the realtime voltage and current time series and the anode *** setting the model time step,the anode effect can be predicted precisely in advance,and the proposed method has good robustness and ***,the traditional Adam algorithm is improved,which enhances the performance and convergence speed of the *** experimental results show that the classification accuracy and F1score of the model are 97.14% and 0.9579%,*** prediction time can reach 15 min.

关键词： Aluminium electrolysis Anode effect prediction Deep learning Improved Adam algorithm Merging model

CNMa-CNMa receptor at microbiome-gut-brain axis:novel target to regulate feeding decision

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Signal Transduction and Targeted Therapy 2021年第8期6卷 2275-2277页

作者： Liyuan peng Hai-Yan yin Canhua Huang School of Basic Medical Sciences Chengdu University of Traditional Chinese MedicineChengduChina State Key Laboratory of Biotherapy and Cancer Center West China Hospitaland West China School of Basic Medical Sciences&Forensic MedicineSichuan Universityand Collaborative Innovation Center for BiotherapyChengduChina lnternational Collaborative Centre on Big Science Plan for Purinergic Signalling Chengdu University of Traditional Chinese MedicineChengduChina Acupuncture and Chronobiology Key Laboratory of Sichuan Province ChengduChina

A recent study published in Nature by Kim et *** that the CNMamide(CNMa)-CNMa receptor(CNMaR)axis plays a crucial regulatory role in response to deprivation of diet-and microbiome-derived amino acid in *** detail,gut enterocytes detect and respond to protein limitation through upregulating CNMa expression and communicating with CNMaR-expressing neurons in the brain(Fig.1).

关键词： CNM expressing

Targets and beyond:cancer stem cell elimination

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Science Bulletin 2017年第16期62卷 1104-1105页

作者： Anqi Wu Guang Shu Jing Wang gang yin Department of Pathology Xiangya HospitalCentral South University Department of Pathology School of Basic Medicine SciencesCentral South University

Cancer stem cells(CSCs)have been reported in various cancer types.A small portion of tumor cells that possess tumor initiation capacity,resist conventional drug treatment and correlate with poor prognosis are believed to be essential to drive tumor progression and ***,successfully targeting CSCs is a promising strategy of cancer treatment.

关键词：肿瘤干细胞癌症治疗肿瘤细胞药物治疗

Experimental Investigation of Bubble Behaviors in Subcooled Flow Boiling

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Journal of Thermal Science 2012年第2期21卷 184-188页

作者： peng Guan Li Jia Liaofei yin Shuo Wang Department of Power Engineering School of Mechanical and Electronic Control Engineering Beijing Jiaotong Univer-sity Shangyuancun No.3 100044 Beijing China

The experimental investigation on vapor bubble growth is performed for analyzing subcooled boiling in a vertical annular channel with inner heating surface and upward water flow under atmospheric pressure. Bulk liquid mass flux ranges from 79 kg/m2s to 316 kg/m2s, and subcooling is from 40 K to 60 K. The bubble behaviors from inception to collapse are captured by High-speed photography. The performance of bubble growth recorded by the high-speed photography is given in this paper. The bubble behaviors, effect of the bubble slippage on the heat transfer, and various forces acting on the bubble are discussed.

关键词： subcooled boiling annular channel bubble behaviors visualization

Sinogram denoising via attention residual dense convolutional neural network for low-dose computed tomography

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Nuclear Science and Techniques 2021年第4期32卷 70-83页

作者： yin-Jin Ma Yong Ren peng Feng peng He Xiao-Dong Guo Biao Wei Key Laboratory of Optoelectronic Technology and Systems Ministry of EducationChongqing UniversityChongqing 400044China School of Data Science Tongren UniversityTongren 554300China School of Microelectronics and Communication Engineering Chongqing UniversityChongqing 400044China Department of Biomedical Engineering Rensselaer Polytechnic InstituteTroyNY 12180USA

The widespread use of computed tomography(CT)in clinical practice has made the public focus on the cumulative radiation dose delivered to ***-dose CT(LDCT)reduces the X-ray radiation dose,yet compromises quality and decreases diagnostic *** have made great efforts to develop various algorithms for LDCT and introduced deep-learning techniques,which have achieved impressive ***,most of these methods are directly performed on reconstructed LDCT images,in which some subtle structures and details are readily lost during the reconstruction procedure,and convolutional neural network(CNN)-based methods for raw LDCT projection data are rarely *** address this problem,we adopted an attention residual dense CNN,referred to as AttRDN,for LDCT sinogram ***,it was aided by the attention mechanism,in which the advantages of both feature fusion and global residual learning were used to extract noise from the contaminated LDCT ***,the denoised sinogram was restored by subtracting the noise obtained from the input noisy ***,the CT image was reconstructed using filtered *** experimental results qualitatively and quantitatively demonstrate that the proposed AttRDN can achieve a better performance than state-of-the-art ***,it can prevent the loss of detailed information and has the potential for clinical application.

关键词： Low-dose CT Sinogram denoising Deep learning Attention mechanism

Nearly Uniform Design Construction on Flexible Region

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Acta Mathematicae Applicatae Sinica 2020年第3期36卷 557-565页

作者： Jian-hui NING Wen-wen yin Li peng School of Mathematics and Statistics Center China Normal UniversityWuhan 430079China School of statistics Renmin University of ChinaBeijing 100872China Department of Statistics General Administration of Customs of the People's Republic of ChinaBeijing 100730China

In this paper,we deduced an iteration formula for the computation of central composite *** using the iteration formula,the computational complexity of uniform design construction in flexible region can be greatly *** we also made a refinement to threshold accepting algorithm to accelerate the algorithm's convergence *** show that the refined algorithm can converge to the lower discrepancy design more stably.

关键词： uniform design flexible region central composite discrepancy threshold accepting algorithm

Sparse recovery in probability via l_q-minimization with Weibull random matrices for 0 < q ≤ 1

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Applied Mathematics(A Journal of Chinese Universities) 2018年第1期33卷 1-24页

作者： GAO Yi peng Ji-gen YUE Shi-gang School of Mathematics and Statistics Xi'an Jiaotong University School of Mathematics and Information Science North Minzu University School of Mathematics and Information Science Guangzhou University School of Computer Science University of Lincoln

Although Gaussian random matrices play an important role of measurement matrices in compressed sensing, one hopes that there exist other random matrices which can also be used to serve as the measurement matrices. Hence, Weibull random matrices induce extensive interest. In this paper, we first propose the lrobust null space property that can weaken the D-RIP, and show that Weibull random matrices satisfy the lrobust null space property with high probability. Besides, we prove that Weibull random matrices also possess the lquotient property with high probability. Finally, with the combination of the above mentioned properties,we give two important approximation characteristics of the solutions to the l-minimization with Weibull random matrices, one is on the stability estimate when the measurement noise e ∈ R~n needs a priori ‖e‖≤ε, the other is on the robustness estimate without needing to estimate the bound of ‖e‖. The results indicate that the performance of Weibull random matrices is similar to that of Gaussian random matrices in sparse recovery.

关键词： compressed sensing l_q-minimization Weibull matrices null space property quotient property