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Quantitative Green's function estimates for lattice quasi-periodic Schrodinger operators

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Science China Mathematics 2024年第5期67卷 1011-1058页

作者： Hongyi cao yunfeng shi Zhifei Zhang School of Mathematical Sciences Peking UniversityBeijing 100871China School of Mathematics Sichuan UniversityChengdu 610064China

In this paper,we establish quantitative Green’s function estimates for some higher-dimensional lattice quasi-periodic(QP)Schrodinger operators.The resonances in the estimates can be described via a pair of symmetric zeros of certain functions,and the estimates apply to the sub-exponential-type non-resonance conditions.As the application of quantitative Green’s function estimates,we prove both the arithmetic version of Anderson localization and the finite volume version of(1/2-)-Holder continuity of the integrated density of states(IDS)for such QP Schrodinger operators.This gives an affirmative answer to Bourgain’s problem in Bourgain(2000).

关键词： Holder continuity of the IDS quantitative Green's function estimates quasi-periodic Schrodinger operators arithmetic Anderson localization multi-scale analysis

A Novel CCA-NMF Whitening Method for Practical Machine Learning Based Underwater Direction of Arrival Estimation

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Journal of Beijing Institute of Technology 2024年第2期33卷 163-174页

作者： yun Wu Xinting Li Zhimin cao School of Physics and Electronic Engineering Northeast Petroleum UniversityDaqing 163318China

Underwater direction of arrival(DOA)estimation has always been a very challenging theoretical and practical problem.Due to the serious non-stationary,non-linear,and non-Gaussian characteristics,machine learning based DOA estimation methods trained on simulated Gaussian noised array data cannot be directly applied to actual underwater DOA estimation tasks.In order to deal with this problem,environmental data with no target echoes can be employed to analyze the non-Gaussian components.Then,the obtained information about non-Gaussian components can be used to whiten the array data.Based on these considerations,a novel practical sonar array whitening method was proposed.Specifically,based on a weak assumption that the non-Gaussian components in adjacent patches with and without target echoes are almost the same,canonical cor-relation analysis(CCA)and non-negative matrix factorization(NMF)techniques are employed for whitening the array data.With the whitened array data,machine learning based DOA estimation models trained on simulated Gaussian noised datasets can be used to perform underwater DOA estimation tasks.Experimental results illustrated that,using actual underwater datasets for testing with known machine learning based DOA estimation models,accurate and robust DOA estimation performance can be achieved by using the proposed whitening method in different underwater con-ditions.

关键词： direction of arrival(DOA) sonar array data underwater disturbance machine learn-ing canonical correlation analysis(CCA) non-negative matrix factorization(NMF)

Recent advances and challenges of nitrogen/nitrate electro catalytic reduction to ammonia synthesis

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Frontiers in Energy 2024年第2期18卷 128-140页

作者： Junwen cao Yikun HU yun ZHENG Wenqiang ZHANG Bo YU Institute of Nuclear and New Energy Technology(INET) Collaborative Innovation Center of Advanced Nuclear Energy TechnologyTsinghua UniversityBeijing 100084China Department of Chemical Engineering University of WaterlooWaterlooOntario N2L 3G1Canada Institute of New Energy Materials and Engineering School of Materials Science and EngineeringFuzhou UniversityFuzhou 350108China

The Haber-Bosch process is the most widely used synthetic ammonia technology at present.Since its invention,it has provided an important guarantee for global food security.However,the traditional Haber-Bosch ammonia synthesis process consumes a lot of energy and causes serious environmental pollution.Under the serious pressure of energy and environment,a green,clean,and sustainable ammonia synthesis route is urgently needed.Electrochemical synthesis of ammonia is a green and mild new method for preparing ammonia,which can directly convert nitrogen or nitrate into ammonia using electricity driven by solar,wind,or water energy,without greenhouse gas and toxic gas emissions.Herein,the basic mechanism of the nitrogen reduction reaction(NRR)to ammonia and nitrate reduction reaction(NO_(3)^(-))to ammonia were discussed.The representative approaches and major technologies,such as lithium mediated electrolysis and solid oxide electrolysis cell(SOEC)electrolysis for NRR,high activity catalyst and advanced electrochemical device fabrication for(NO_(3)^(-))RR and electrochemical ammonia synthesis were summarized.Based on the above discussion and analysis,the main challenges and development directions for electrochemical ammonia synthesis were further proposed.

关键词： electrochemical ammonia synthesis nitrogen nitrate nitrogen reduction reaction(NRR)to ammonia nitrate reduction reaction(NO_(3)^(-))RR

Adaptive 5G-and-beyond network-enabled interpretable federated learning enhanced by neuroevolution

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Science China(Information Sciences) 2024年第7期67卷 107-132页

作者： Bin cao Jianwei ZHAO Xin LIU yun LI State Key Laboratory of Reliability and Intelligence of Electrical Equipment Hebei University of Technology School of Artificial Intelligence Hebei University of Technology School of Economics and Management Hebei University of Technology Industrial Artificial Intelligence Centre Shenzhen Institute for Advanced StudyUniversity of Electronic Science and Technology of China

Mobile telemedicine systems based on the next-generation communication will significantly enhance deep fusion of network automation and federated learning(FL), but data privacy is a paramount issue in sectors like healthcare. This work hence considers FL augments 5G-and-beyond networks by training deep learning(DL) models without the need to exchange raw data. The substantial communication loads imposed on by extensive parameters involved in DL models are managed through adaptive scheduling mechanisms effectively. To address the opaque nature of DL models and to improve the interpretability of FL models, we introduce a convolutional fuzzy rough neural network specifically designed for medical image processing. We also develop a multiobjective memetic evolutionary algorithm to streamline and optimize the neural network architectures. Our comprehensive FL framework integrates smart scheduling, interpretable fuzzy rough logic,and neuroevolution. This framework is shown to improve communication efficiency, increase interpretability of diagnosis with protected privacy, and generate low-complexity neural architectures.

关键词： 5G-and-beyond network interpretable federated learning mobile telemedicine system fuzzy rough set theory neuroevolution

Artificial intelligence for the detection of glaucoma with SD-OCT images:a systematic review and Meta-analysis

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International Journal of Ophthalmology(English edition) 2024年第3期17卷 408-419页

作者： Nan-Nan shi Jing Li Guang-Hui Liu Ming-Fang cao Department of Ophthalmology Affiliated People’s Hospital(Fujian Provincial People’s Hospital)Fujian University of Traditional Chinese MedicineFuzhou 350004Fujian ProvinceChina Eye Institute of Integrated Chinese and Western Medicine Fujian University of Traditional Chinese MedicineFuzhou 350004Fujian ProvinceChina

●AIM:To quantify the performance of artificial intelligence(AI)in detecting glaucoma with spectral-domain optical coherence tomography(SD-OCT)images.●METHODS:Electronic databases including PubMed,Embase,Scopus,ScienceDirect,ProQuest and Cochrane Library were searched before May 31,2023 which adopted AI for glaucoma detection with SD-OCT images.All pieces of the literature were screened and extracted by two investigators.Meta-analysis,Meta-regression,subgroup,and publication of bias were conducted by Stata16.0.The risk of bias assessment was performed in Revman5.4 using the QUADAS-2 tool.●RESULTS:Twenty studies and 51 models were selected for systematic review and Meta-analysis.The pooled sensitivity and specificity were 0.91(95%CI:0.86–0.94,I2=94.67%),0.90(95%CI:0.87–0.92,I2=89.24%).The pooled positive likelihood ratio(PLR)and negative likelihood ratio(NLR)were 8.79(95%CI:6.93–11.15,I2=89.31%)and 0.11(95%CI:0.07–0.16,I2=95.25%).The pooled diagnostic odds ratio(DOR)and area under curve(AUC)were 83.58(95%CI:47.15–148.15,I2=100%)and 0.95(95%CI:0.93–0.97).There was no threshold effect(Spearman correlation coefficient=0.22,P>0.05).●CONCLUSION:There is a high accuracy for the detection of glaucoma with AI with SD-OCT images.The application of AI-based algorithms allows together with“doctor+artificial intelligence”to improve the diagnosis of glaucoma.

关键词： artificial intelligence spectral-domain optical coherence tomography glaucoma Meta-analysis

Deep decalcification of factory-provided freezing acidolysis solution to achieveα-high-strength gypsum

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Chinese Journal of Chemical Engineering 2024年第5期69卷 143-151页

作者： Wencai Ye Yulu Li Yonggang Dong Lin Yang yun Yi Jianxin cao School of Chemistry and Chemical Engineering Guizhou UniversityGuiyang 550025China Engineering Research Center of Efficient Utilization for Industrial Waste Guizhou UniversityGuiyang 550025China Key Laboratory of Guizhou Province for Green Chemical Industry and Clean Energy Technology Guizhou UniversityGuiyang 550025China

The freezing acidolysis solution of the nitric acid-phosphate fertilizer process has a high calcium content,which makes it difficult to produce fine phosphate and high water-soluble phosphate fertilizer products.Here,based on the potential crystallization principle of calcium sulfate in NH_(4)NO_(3)-H_(3)PO_(4)-H_(2)O,the deep decalcification(i.***.calcium removal)technology to achieveα-high-strength gypsum originated from freezing acidolysis-solutions has been firstly proposed and investigated.Typically,calcium can be removed from the factory-provided freezing acidolysis-solution by neutralizing it with ammonia,followed by the addition of ammonium sulfate solution.As a result,the formation of calcium sulfate in the reaction system undergoes the nucleation and growth of CaSO_(4)·2H_(2)O(DH),as well as its dissolution and crystallization into short columnarα-CaSO_(4)·0.5H_(2)O(α-HH).Remarkably,with the molar ratio of SO_(4)^(2-)/Ca^(2+)at 1.8,the degree of neutralization(NH_(3)/HNO_(3) molar ratio)at 1.7,the reaction temperature of 94℃,and the reaction time of 300 min,the decalcification rate can reach 86.89%,of which the high-strengthα-CaSO_(4)·0.5H_(2)O(α-HH)will be obtained.Noteworthy,the deep decalcification product meets the standards for the production of fine phosphates and highly water-soluble phosphate fertilizers.Consequently,the 2 h flexural strength ofα-HH is 5.3 MPa and the dry compressive strength is 36.8 MPa,which is up to the standard of commercialα-HH.

关键词： Nitrophosphate Ammonia neutralization Deep decalcification High-strengthα-hemihydrate gypsum Controlled crystallization at atmospheric pressure

Analysis of mechanical strengths of extreme line casing joint considering geometric, material, and contact nonlinearities

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Petroleum Science 2024年第3期21卷 1992-2004页

作者： Ji-yun Zhang Chi Peng Jian-Hong Fu Quan cao Yu Su Jian-yun Pang Zi-Qiang Yu Petroleum Engineering School Southwest Petroleum University Engineering Technology Research Institute of CNPC Southwest Oil and Gas Field Company

To address the challenges associated with difficult casing running, limited annular space, and poor cementing quality in the completion of ultra-deep wells, the extreme line casing offers an effective solution over conventional casings. However, due to its smaller size, the joint strength of extreme line casing is reduced, which may cause failure when running in the hole. To address this issue, this study focuses on the CST-ZT Φ139.7 mm × 7.72 mm extreme line casing and employs the elastic-plastic mechanics to establish a comprehensive analysis of the casing joint, taking into account the influence of geometric and material nonlinearities. A finite element model is developed to analyze the forces and deformations of the extreme line casing joint under axial tension and external collapse load. The model investigates the stress distribution of each thread tooth subjected to various tensile forces and external pressures. Additionally, the tensile strength and crushing strength of the extreme line casing joint are determined through both analytical and experimental approaches. The findings reveal that, under axial tensile load, the bearing surface of each thread tooth experiences uneven stress, with relatively high equivalent stress at the root of each thread tooth. The end thread teeth are valuable spots for failure. It is observed that the critical fracture axial load of thread decreases linearly with the increase of thread tooth sequence. Under external pressure, the circumferential stress is highest at the small end of the external thread, leading to yield deformation. The tensile strength of the joint obtained from the finite element model exhibits a relative error of less than 7% compared to the analytical and experimental values,proving the reliability of the finite element model. The tensile strength of the joint is 3091.9 k N.Moreover, in terms of anti-collapse capability, the joints demonstrate higher resistance to collapse compared to the casing body, which is consistent with the test results where the pip

关键词： Extreme line casing Elastic-plastic mechanics Finite element analysis Tensile strength Collapse strength

Synthetic host-guest pairs as novel bioorthogonal tools for pre-targeting

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Chinese Chemical Letters 2024年第2期35卷 44-56页

作者： Yan-Long Ma shi Yan Xiong-Jie Xu Hua cao Ruibing Wang School of Chemistry and Chemical Engineering and Guangdong Cosmetics Engineering & Technology Research Center Guangdong Pharmaceutical UniversityZhongshan 528458China State Key Laboratory of Quality Research in Chinese Medicine and the Institute of Chinese Medical ScienceUniversity of MacaoMacao 999078China

Due to its simplicity, high efficiency, and chemo-selectivity, bioorthogonal chemistry has shown a great application potential in pre-targeting.Currently, four bioorthogonal pairs as targeting tools, including (strept)avidin/biotin, antibody/antigen, oligonucleotide hybridization and IEDDA tools, have been developed and applied in targeted delivery.Nevertheless, all of these tools still suffer from some limitations, such as difficult modification, biochemical fragility and larger molecular weight for biological association tools, as well as chemical instability for IEDDA tools.Synthetic host-guest pairs with relatively small molecular sizes not only possess strong chemical stability, but also have the features of fast conjugation rate, tunable binding affinity , easy modification, and high chemo-selectivity.Consequently, they can be used as a novel non-covalent bioorthogonal tool for pre-targeting.In order to further promote the development of host-guest pairs as novel bioorthogonal tools for pre-targeted delivery, we firstly calculate their conversion rate to make researcher aware of their unique advantages;next, we summarize the recent research progress in this area.The future perspectives and limitations of these unique tools will be discussed.This review will provide a systemic overview of the development of synthetic host-guest pairs as novel bioorthogonal tools for pre-targeting, and may serve as a “go for” resort for researchers who are interested in searching for new synthetic tools to improve pre-targeting.

关键词： Bioorthogonal chemistry Synthetic host-guest pairs Pre-targeting Molecular recognition Biomedical applications

Prediction of chemical short-range order in high-/medium-entropy alloys

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Journal of Materials Science & Technology 2024年第2期169卷 115-123页

作者： Pei-Yu cao Jing Wang Ping Jiang yun-Jiang Wang Fu-Ping Yuan Xiao-Lei Wu State Key Laboratory of Nonlinear Mechanics Institute of MechanicsChinese Academy of ScienceBeijing 100190China School of Engineering Science University of Chinese Academy of SciencesBeijing 100049China

Chemical short-range orders(CSROs),as the built-in sub-nanoscale entities in a high-/medium-entropy alloy(H/MEA),have aroused an ever-increasing interest.With multi-principal elements in an H/MEA to form a complex concentrated solution,a variety of sub-systems of species exist to induce the metastable ordered compounds as candidates for ultimate CSROs.The issues remain pending on the origin of CSROs as to how to judge if CSRO will form in an H/MEA and particularly,what kind of CSROs would be stably produced if there were multiple possibilities.Here,the first-principles method,along with the proposed local formation energy calculation in allusion to the atomic-scale chemical heterogeneities,is used to predict the CSRO formation based on the mechanical stability,thermodynamic formation energy,and electronic characteristics.The simulations are detailed in an equiatomic ternary VCoNi MEA with three kinds of potential compounds,i.e.,L1_(1),L1_(2),and B2,in the face-centered cubic matrix.It turns out that L1_(1)is stable but hard to grow up so as to become the final CSRO.L1_(1)is further predicted as CSROs in CrCoNi,but unable to form in FeCoNi and CrMnFeCoNi alloys.These predictions are consistent with the experimental observations.Our findings shed light on understanding the formation of CSROs.This method is applicable to other H/MEAs to design and tailor CSROs by tuning chemical species/contents and thermal processing for high performance.

关键词： Short-range order High-entropy alloy Microstructure First-principles calculation Gibbs free energy Local electronic density of states