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Study on Coded Permutation Entropy of Finite Length Gaussian White Noise Time Series

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Chinese Journal of Electronics 2024年第1期33卷 185-194页

作者： Huihui sun Xiaofeng zhang School of Physics and Information Technology Shaanxi Normal University

As an extension of permutation entropy(PE), coded permutation entropy(CPE) improves the performance of PE by making a secondary division for ordinal patterns defined in PE. In this study, we provide an exploration of the statistical properties of CPE using a finite length Gaussian white noise time series theoretically. By means of the Taylor series expansion, the approximate expressions of the expected value and variance of CPE are deduced and the Cramér-Rao low bound(CRLB) is obtained to evaluate the performance of the CPE estimator. The results indicate that CPE is a biased estimator, but the bias only depends on relevant parameters of CPE and it can be easily corrected for an arbitrary time series. The variance of CPE is related to the encoding patterns distribution,and the value converges to the CRLB of the CPE estimator when the time series length is large enough. For a finitelength Gaussian white noise time series model, the predicted values can match well with the actual values, which further validates the statistic theory of CPE. Using the theoretical expressions of CPE, it is possible to better understand the behavior of CPE for most of the time series.

关键词： Coded permutation entropy Gaussian white noise Finite-length time series Cramér-Rao low bound

Complex adaptive system theory,agent-based modeling,and simulation in dominant technology formation

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Journal of Systems Engineering and Electronics 2024年第1期35卷 130-153页

作者： zhang Ruihan sun Bing Glorious sun School of Business and Management Donghua UniversityShanghai 200051China School of Economics and Management Harbin Engineering UniversityHarbin 150001China

Dominant technology formation is the key for the hightech industry to“cross the chasm”and gain an established foothold in the market(and hence disrupt the regime).Therefore,a stimulus-response model is proposed to investigate the dominant technology by exploring its formation process and mechanism.Specifically,based on complex adaptive system theory and the basic stimulus-response model,we use a combination of agent-based modeling and system dynamics modeling to capture the interactions between dominant technology and the socio-technical landscape.The results indicate the following:(i)The dynamic interaction is“stimulus-reaction-selection”,which promotes the dominant technology’s formation.(ii)The dominant technology’s formation can be described as a dynamic process in which the adaptation intensity of technology standards increases continuously until it becomes the leading technology under the dual action of internal and external mechanisms.(iii)The dominant technology’s formation in the high-tech industry is influenced by learning ability,the number of adopting users and adaptability.Therein,a“critical scale”of learning ability exists to promote the formation of leading technology:a large number of adopting users can promote the dominant technology’s formation by influencing the adaptive response of technology standards to the socio-technical landscape and the choice of technology standards by the socio-technical landscape.There is a minimum threshold and a maximum threshold for the role of adaptability in the dominant technology’s formation.(iv)The socio-technical landscape can promote the leading technology’s shaping in the high-tech industry,and different elements have different effects.This study promotes research on the formation mechanism of dominant technology in the high-tech industry,presents new perspectives and methods for researchers,and provides essential enlightenment for managers to formulate technology strategies.

关键词： complex adaptive system theory agent-based modeling and simulation dominant technology socio-technical landscape adaptation-choice

Microbiome and intestinal pathophysiology in post-acute sequelae of COVID-19

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Genes & Diseases 2024年第3期11卷 220-231页

作者： Jilei zhang Yongguo zhang Yinglin Xia Jun sun Division of Gastroenterology and Hepatology Department of MedicineUniversity of Ilinois ChicagoIL60612USA Uic Cancer Center Department of Microbiology and ImmunologyUniversity of Ilinois ChicagoChicagoIL60612USA Jesse Brown VA Medical Center ChicagoIL60612USA

Long CoVID,also known for post-acute sequelae of CovID-19,describes the people who have the signs and symptoms that continue or develop after the acute coviD-19 phase.Long CovID patients suffer from an inflammation or host responses towards the virus approx-imately 4 weeks after initial infection with the SARS CoV-2 virus and continue for an unchar-acterized duration.Anyone infected with CovID-19 before could experience long-CcovID conditions,including the patients who were infected with SARS CoV-2 virus confirmed by tests and those who never knew they had an infection early.People with long CoviD may experience health problems from different types and combinations of symptoms over time,such as fa-tigue,dyspnea,cognitive impairments,and gastrointestinal(Gl)symptoms(e.g.,nausea,vom-iting,diarrhea,decreased or loss of appetite,abdominal pain,and dysgeusia).The critical role of the microbiome in these Gl symptoms and long CovID were reported in clinical patients and experimental models.Here,we provide an overall view of the critical role of the Gl tract and microbiome in the development of long COVID,including the clinical Gl symptoms in patients,dysbiosis,viral-microbiome interactions,barrier function,and inflammatory bowel disease patients with long CovID.We highlight the potential mechanisms and possible treatment based on Gl health and microbiome.Finally,we discuss challenges and future direction in the long CoVID clinic and research.

关键词： Gastrointestinal symptoms Gl tract Gut microbiome Inflammatorybowel diseases Intestinal barrier Long CoVID Metabolites Tight junctions

Effect of wire mesh casing treatment on axial compressor performance and stability

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Chinese Journal of Aeronautics 2024年第3期37卷 60-76页

作者： Ming zhang Jiaming zhang Jiahao HU Xu DONG Dakun sun Xiaofeng sun School of Energy and Power Engineering Beihang UniversityBeijing 100191China Beihang Hangzhou Innovation Institute Yuhang Hangzhou 310023China National Key Laboratory of Science and Technology on Aero-Engine Aero-Thermodynamics Beihang UniversityBeijing 100191China

In this paper,a kind of Wire Mesh Casing Treatment(WMCT)is proposed to improve the stable operating range of the compressor.In contrast to the traditional circumferential groove,as for WMCT,a layer of wire mesh is laid on the surface of the circumferential groove.Parametric studies were conducted on the low-speed axial flow compressor,including the groove width,axial location,and mesh count.The optimum axial location for WMCT is related to its groove width.A higher wire mesh count results in a smaller compressor stall margin improvement.Steady simulations were carried out to study the effect of WMCT on the flow structure of the compressor.The wire mesh in the WMCT has a certain flow resistance,which restricts the flow into and out of the groove.Due to the WMCT,the flow parameter in the tip region of the rotor is less sensitive to changes in the operating conditions of the compressor.The WMCT causes the rotor tip blade loading to shift backward,inhibiting the formation of spill forward of the leakage flow,and thus improving the stability of the compressor.The flow resistance on the groove surface is a new degree-of-freedom for the casing treatment designer.

关键词： Axial compressor Wire mesh casing treatment Tip clearance flow Stall margin Blade loading

ONE-PARAMETER FINITE DIFFERENCE METHODS AND THEIR ACCELERATED SCHEMES FOR SPACE-FRACTIONAL SINE-GORDON EQUATIONS WITH DISTRIBUTED DELAY

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Journal of Computational Mathematics 2024年第3期42卷 705-734页

作者： Tao sun Chengjian zhang Haiwei sun School of Mathematics and Statistics Huazhong University of Science and TechnologyWuhan 430074China Hubei Key Laboratory of Engineering Modeling and Scientific Computing Huazhong University of Science and TechnologyWuhan 430074China Department of Mathematics University of MacaoMacaoChina

This paper deals with numerical methods for solving one-dimensional(1D)and twodimensional(2D)initial-boundary value problems(IBVPs)of space-fractional sine-Gordon equations(SGEs)with distributed delay.For 1D problems,we construct a kind of oneparameter finite difference(OPFD)method.It is shown that,under a suitable condition,the proposed method is convergent with second order accuracy both in time and space.In implementation,the preconditioned conjugate gradient(PCG)method with the Strang circulant preconditioner is carried out to improve the computational efficiency of the OPFD method.For 2D problems,we develop another kind of OPFD method.For such a method,two classes of accelerated schemes are suggested,one is alternative direction implicit(ADI)scheme and the other is ADI-PCG scheme.In particular,we prove that ADI scheme can arrive at second-order accuracy in time and space.With some numerical experiments,the computational effectiveness and accuracy of the methods are further verified.Moreover,for the suggested methods,a numerical comparison in computational efficiency is presented.

关键词： Fractional sine-Gordon equation with distributed delay One-parameter finite difference methods Convergence analysis ADI scheme PCG method

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Light(Science & Applications) 2024年第2期13卷 333-346页

作者： Yifan sun Qian Li Ling-Jun Kong Xiangdong zhang Key Laboratory of advanced optoelectronic quantum architecture and measurements of Ministry of Education Beijing Key Laboratory of Nanophotonics&Ultrafine Optoelectronic SystemsSchool of PhysicsBeijing Institute of Technology100081BeijingChina

Compared with electrical neural networks,optical neural networks(ONNs)have the potentials to break the limit of the bandwidth and reduce the consumption of energy,and therefore draw much attention in recent years.By far,several types of ONNs have been implemented.However,the current ONNs cannot realize the acceleration as powerful as that indicated by the models like quantum neural networks.How to construct and realize an ONN with the quantum speedup is a huge challenge.Here,we propose theoretically and demonstrate experimentally a new type of optical convolutional neural network by introducing the optical correlation.It is called the correlated optical convolutional neural network(COCNN).We show that the COCNN can exhibit“quantum speedup”in the training process.The character is verified from the two aspects.One is the direct illustration of the faster convergence by comparing the loss function curves of the COCNN with that of the traditional convolutional neural network(CNN).Such a result is compatible with the training performance of the recently proposed quantum convolutional neural network(QCNN).The other is the demonstration of the COCNN’s capability to perform the QCNN phase recognition circuit,validating the connection between the COCNN and the QCNN.Furthermore,we take the COCNN analog to the 3-qubit QCNN phase recognition circuit as an example and perform an experiment to show the soundness and the feasibility of it.The results perfectly match the theoretical calculations.Our proposal opens up a new avenue for realizing the ONNs with the quantum speedup,which will benefit the information processing in the era of big data.

关键词： process quantum convolution

Jackknife Model Averaging for Quantile Single-Index Coefficient Model

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Journal of Systems Science & Complexity 2024年第4期37卷 1685-1713页

作者： sun Xianwen zhang Lixin School of Mathematical Sciences Zhejiang University School of Statistics and Mathematics Zhejiang Gongshang University

In the past two decades, model averaging, as a way to solve model uncertainty, has attracted more and more attention. In this paper, the authors propose a jackknife model averaging(JMA)method for the quantile single-index coefficient model, which is widely used in statistics. Under model misspecification, the model averaging estimator is proved to be asymptotically optimal in terms of minimizing out-of-sample quantile loss. Simulation experiments are conducted to compare the JMA method with several model selections and model averaging methods, and the results show that the proposed method has a satisfactory performance. The method is also applied to a real dataset.

关键词： Final prediction error JMA criterion model averaging quantile loss single-index coefficient model

A combined evaluation of the characteristics and antibiotic resistance induction potential of antibiotic wastewater during the treatment process

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Journal of Environmental Sciences 2024年第4期138卷 626-636页

作者： sun Miao Yanyan zhang Cong Men Yiou Mao Jiane Zuo State Key Joint Laboratory of Environment Simulation and Pollution Control School of EnvironmentTsinghua UniversityBeijing 100084China School of Energy and Environmental Engineering Beijing Key Laboratory of Resource-Oriented Treatment of Industrial PollutantsUniversity of Science and Technology BeijingBeijing 100083China High School Affiliated to Renmin University of China Beijing 100080China Tsinghua Shenzhen International Graduate School Shenzhen 518055China

Antibiotic wastewater contains a variety of pollutant stressors that can induce and promote antibiotic resistance(AR)when released into the environment.Although these substances are mostly in concentrations lower than those known to induce AR individually,it is possible that antibiotic wastewater discharge might still promote the AR transmission risk via additive or synergistic effects.However,the comprehensive effect of antibiotic wastewater on AR development has rarely been evaluated,and its treatment efficiency remains unknown.Here,samples were collected from different stages of a cephalosporin production wastewater treatment plant,and the potential AR induction effect of their chemical mixtures was explored through the exposure of the antibiotic-sensitive Escherichia coli K12 strain.Incubation with raw cephalosporin production wastewater significantly promoted mutation rates(3.6×10^(3)-9.3×10^(3)-fold)and minimum inhibition concentrations(6.0-6.7-fold)of E.coli against ampicillin and chloramphenicol.This may be attributed to the inhibition effect and oxidative stress of cephalosporin wastewater on E.coli.The AR induction effect of cephalosporin wastewater decreased after the coagulation sedimentation treatment and was completely removed after the full treatment process.A Pearson correlation analysis revealed that the reduction in the AR induction effect had a strong positive correlation with the removal of organics and biological toxicity.This indicates that the antibiotic wastewater treatment had a collaborative processing effect of conventional pollutants,toxicity,and the AR induction effect.This study illustrates the potential AR transmission risk of antibiotic wastewater and highlights the need for its adequate treatment.

关键词： Antibiotic wastewater treatment plant Antibiotic resistance Antibiotic resistance induction effect Correlation analysis Biological toxicity

Exploring changes of precipitation extremes under climate change through global variable-resolution modeling

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Science Bulletin 2024年第2期69卷 237-247页

作者： Wei sun Jian Li Rucong Yu Nina Li Yi zhang State Key Laboratory of Severe Weather Chinese Academy of Meteorological SciencesBeijing 100081China Institute of Tibetan Plateau Meteorology China Meteorological AdministrationChengdu 610072China Department of Atmospheric Science Yunnan UniversityKunming 650091China National Meteorological Center China Meteorological AdministrationBeijing 100081China 2035 Future Laboratory PIESAT Information Technology Co.Ltd.Beijing 100105China

Understanding the responses of precipitation extremes to global climate change remains limited owing to their poor representations in models and complicated interactions with multi-scale systems.Here we take the record-breaking precipitation over China in 2021 as an example,and study its changes under three different climate scenarios through a developed pseudo-global-warming(PGW)experimental framework with 60-3 km variable-resolution global ensemble modeling.Compared to the present climate,the precipitation extreme under a warmer(cooler)climate increased(decreased)in intensity,coverage,and total amount at a range of 24.3%-37.8%(18.7%-56.1%).With the help of the proposed PGW experimental framework,we further reveal the impacts of the multi-scale system interactions in climate change on the precipitation extreme.Under the warmer climate,large-scale water vapor transport converged from double typhoons and the subtropical high marched into central China,enhancing the convective energy and instability on the leading edge of the transport belt.As a result,the mesoscale convective system(Mcs)that directly contributed to the precipitation extreme became stronger than that in the present climate.On the contrary,the cooler climate displayed opposite changing characteristics relative to the warmer climate,ranging from the large-scale systems to local environments and to the Mcs.In summary,our study provides a promising approach to scientifically assess the response of precipitation extremes to climate change,making it feasible to perform ensemble simulations while investigating the multi-scale system interactions over the globe.

关键词： Precipitation extreme Climate change Pseudo-global-warming experiment Variable-resolution modeling Multi-scale system interaction