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Information and knowledge behind data from underground rock grouting

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Journal of Rock Mechanics and Geotechnical Engineering 2021年第6期13卷 1326-1339页

作者： Fei XIAO Qian Liu Zhiye Zhao Department of Civil Engineering Nanjing University of Aeronautics and AstronauticsNanjing210016China School of Civil and Environmental Engineering Nanyang Technological University50 Nanyang Avenue639798Singapore

Data related to the pre-grouting work of a large underground project are systematically analyzed to reveal the mechanism behind,to shed some light on the execution of practical grouting,and to enrich the theory of engineering geology.Grouting is generally taken as an effective way for controlling nonignorable water seepage during underground rock excavation.Though various models have been developed to guide grouting design or to specify criteria for grouting stop,it does not change the fact that grouting is still highly experience-based.Therefore,explanation of the current situation due to grouting complexity is given through step-by-step data analysis,where the impact on grouting parameters from the geological and hydrogeological conditions is investigated,and the grouting features of two tunnels located at the same depth below the sea surface are compared and discussed.Then,the data from individual grout hole are used to construct the regional geological conditions via inverse analysis.It is found that grouting of fractured rock masses is accompanied with great uncertainty,and field grouting data can contribute significantly to a better understanding of the regional geological conditions around an underground tunnel or rock cavern.

关键词： Field grouting data Water seepage Rock grouting Inverse modelling Data analytics Geological conditions

High-temperature CO_(2) sorbents with citrate and stearate intercalated Ca-Al hydrotalcite-like as precursor

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Chinese Journal of Chemical Engineering 2022年第10期50卷 177-184页

作者： Tao Jiang Fei XIAO Yujun Zhao Shengping Wang Xinbin Ma Key Laboratory for Green Chemical Technology School of Chemical Engineering and TechnologyCollaborative Innovation Center of Chemical Science and Engineering(Tianjin)Tianjin UniversityTianjin 300072China

CO_(2),one of the main components of greenhouse gases,increased rapidly because of the growing use of fossil fuels.And CaO sorbents possess the capability to be used in capture of CO_(2) at high temperature.In the work,Ca-Al complex oxides derived from citrate and stearate intercalated layered double hydroxides were fabricated and their CO_(2) adsorption capacity was compared with that from CO_(3)^(2-)intercalated layered double hydroxides.The results presented that the sorbents(Ca/Al=5)with Ca-Al-citrate layered double hydroxides as precursors performed best and displayed remarkable CO_(2) capture capacity of 52.0%(mass)at the carbonization temperature of 600℃without distinct recession during cycling adsorption/desorption tests.The excellent CO_(2) adsorption capacity of the sorbent was ascribed to its smaller crystallite size of calcinated particles,optimized pore size distribution as well as homogeneous distributed Ca and Al in the sorbent.

关键词： Layered doublehydroxides CO_(2)capture CaO-based Organic ions

Modeling the redshift and energy distributions of fast radio bursts

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Research in Astronomy and Astrophysics 2017年第2期17卷 22-28页

作者： xiao-Feng Cao Ming xiao Fei XIAO Department of Physics and Engineering Hubei University of Education Wuhan 430205 China

Abstract Fast radio bursts （FRBs） are one of the most mysterious astronomical phenomena nowadays. The identification of their origin requires more observations in the future and, importantly, deep un- derstandings of the existing observational data. By fitting the redshift and energy distributions of 15 Parkes FRBs, we try to derive their intrinsic energy function and the cosmic evolution of their burst rates. Specifically, while the energy function is assumed as usual to have a single-power-law form, the burst rates are considered to be proportional to the cosmic star formation rates by a redshift-dependent coefficient. Some plausible fittings are obtained, which indicate the power-law assumptions are feasible and effective. The values of the power-law indices could be used to independently constrain candidate FRB models, although parameter degeneracies still exist.

关键词： radio continuum general

Torque estimation for robotic joint with harmonic drive transmission based on system dynamic characteristics

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Journal of Systems Engineering and Electronics 2022年第6期33卷 1320-1331页

作者： ZHU Minghong xiao Shu YU fei Faculty of Electrical Engineering and Computer Science Ningbo UniversityNingbo 315211China College of Intelligent Systems Science and Engineering Harbin Engineering UniversityHarbin 150001China College of Mathematical Sciences Harbin Engineering UniversityHarbin 150001China

In the applications of joint control and robot movement,the joint torque estimation has been treated as an effective technique and widely used.Researches are made to analyze the kinematic and compliance model of the robot joint with harmonic drive to acquire high precision torque output.Through analyzing the structures of the harmonic drive and experiment apparatus,a scheme of the proposed joint torque estimation method based on both the dynamic characteristics and unscented Kalman filter(UKF)is designed and built.Based on research and scheme,torque estimation methods in view of only harmonic drive compliance model and compliance model with the Kalman filter are simulated as guidance and reference to promote the research on the torque estimation technique.Finally,a promoted torque estimation method depending on both harmonic drive compliance model and UKF is designed,and simulation results compared with the measurements of a commercial torque sensor,have verified the effectiveness of the proposed method.

关键词： harmonic drive torque estimation compliance model unscented Kalman filter(UKF)

Self-supervised coarse-to-fine monocular depth estimation using a lightweight attention module

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Computational Visual Media 2022年第4期8卷 631-647页

作者： Yuanzhen Li fei Luo Chunxia xiao School of Computer Science Wuhan UniversityWuhan 430072China

Self-supervised monocular depth estimation has been widely investigated and applied in previous works.However,existing methods suffer from texture-copy,depth drift,and incomplete structure.It is difficult for normal CNN networks to completely understand the relationship between the object and its surrounding environment.Moreover,it is hard to design the depth smoothness loss to balance depth smoothness and sharpness.To address these issues,we propose a coarse-to-fine method with a normalized convolutional block attention module(NCBAM).In the coarse estimation stage,we incorporate the NCBAM into depth and pose networks to overcome the texture-copy and depth drift problems.Then,we use a new network to refine the coarse depth guided by the color image and produce a structure-preserving depth result in the refinement stage.Our method can produce results competitive with state-of-the-art methods.Comprehensive experiments prove the effectiveness of our two-stage method using the NCBAM.

关键词： monocular depth estimation texture copy depth drift attention module

A Missense Mutation in Epsilon-subunit of Acetylcholine Receptor Causing Autosomal Dominant Slow-channel Congenital Myasthenic Syndrome in a Chinese Family

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Chinese Medical Journal 2016年第21期129卷 2596-2602页

作者： Jia-Ze Tan Yuan Man Fei XIAO Department of Neurology The First Affiliated Hospital of Chongqing Medical University Chongqing Key Laboratory of Neurology Chongqing 400016 China

Background：Congenital myasthenic syndromes are a group orrare disorders that are clinically and genetically heterogeneous and caused by mutations in the genes encoding proteins of the neuromuscular junction.Here,we described a Chinese family that presented with phenotypes of classic slow-channel congenital myasthenic syndrome （SCCMS）.Methods：Clinical characteristics and electrophysiological features of three patients from a Chinese family were examined,and next-generation sequencing followed by direct sequencing was carried out.Results：The patients revealed variability in clinical and electrophysiological features.However,weakness,scoliosis,and repetitive-compound muscle action potential were found in all affected members in the family.A heterozygous C〉T missense mutation at nucleotide 865 in acetylcholine receptor epsilon-subunit （CHRNE） gene that causes a leucine-to-phenylalanine substitution at position 289 （L289F） was found.Conclusions：We reported a SCCMS family of Chinese origin.In the family,classical clinical phenotype with phenotypic variability among different members was found.Genetic testing could help diagnose this rare disease.

关键词： Acetylcholine Receptor Epsilon-subunit Gene Repetitive-compound Muscle Action Potential Repetitive NerveStimulation Slow-channel Congenital Myasthenie Syndrome

Artificial intelligence for COVID-19: battling the pandemic with computational intelligence

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Intelligent Medicine 2022年第1期2卷 13-29页

作者： Zhenxing Xu Chang Su Yunyu xiao fei Wang Department of Population Health Sciences Weill Cornell MedicineCornell UniversityNew York 10065United States Department of Health Service Administration and Policy Temple UniversityPhiladelphia 19122United States

The new coronavirus disease 2019(COVID-19)has become a global pandemic leading to over 180 million confirmed cases and nearly 4 million deaths until June 2021,according to the World Health Organization.Since the initial report in December 2019,COVID-19 has demonstrated a high transmission rate(with an R_(0)>2),a diverse set of clinical characteristics(e.g.,high rate of hospital and intensive care unit admission rates,multi-organ dysfunction for critically ill patients due to hyperinflammation,thrombosis,etc.),and a tremendous burden on health care systems around the world.To understand the serious and complex diseases and develop effective control,treatment,and prevention strategies,researchers from different disciplines have been making significant efforts from different aspects including epidemiology and public health,biology and genomic medicine,as well as clinical care and patient management.In recent years,artificial intelligence(AI)has been introduced into the healthcare field to aid clinical decision-making for disease diagnosis and treatment such as detecting cancer based on medical images,and has achieved superior performance in multiple data-rich application scenarios.In the COVID-19 pandemic,AI techniques have also been used as a powerful tool to overcome the complex diseases.In this context,the goal of this study is to review existing studies on applications of AI techniques in combating the COVID-19 pandemic.Specifically,these efforts can be grouped into the fields of epidemiology,therapeutics,clinical research,social and behavioral studies and are summarized.Potential challenges,directions,and open questions are discussed accordingly,which may provide new insights into addressing the COVID-19 pandemic and would be helpful for researchers to explore more related topics in the post-pandemic era.

关键词： COVID-19 pandemic Artificial intelligence Electronic health record Machine learning

ChatGPT Chats on Computational Experiments:From Interactive Intelligence to Imaginative Intelligence for Design of Artificial Societies and Optimization of Foundational Models

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IEEE/CAA Journal of Automatica Sinica 2023年第6期10卷 1357-1360页

作者： xiao Xue Xiangning Yu fei-Yue Wang College of Intelligence and Computing Tianjin UniversityTianjin 300350China State Key Laboratory for Management and Control of Complex Systems the Institute of Automdtion of Chinese Academg of SciencesBeijing 100190China

POWERED by the rapid development of Internet,the penetration of the Internet of Things,the emergence of big data,and the rise of social media,more and more complex systems are exhibiting the characteristics of social,physical,and information fusion.These systems are known as cyber-physicalsocial systems(CPSS)[1],[2].These CPSS face unprecedented challenges in design,analysis,management,control and integration due to their involvement with human and social factors[3],[4].To cope with this challenge,there are two main approaches to CPSS research.

关键词： Intelligence Foundation involvement

An efficient parallel algorithm of variational nodal method for heterogeneous neutron transport problems

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Nuclear Science and Techniques 2024年第4期35卷 29-45页

作者： Han Yin xiao-Jing Liu Teng-fei Zhang School of Nuclear Science and Engineering Shanghai Jiao Tong UniversityShanghai 2002040China

The heterogeneous variational nodal method(HVNM)has emerged as a potential approach for solving high-fidelity neutron transport problems.However,achieving accurate results with HVNM in large-scale problems using high-fidelity models has been challenging due to the prohibitive computational costs.This paper presents an efficient parallel algorithm tailored for HVNM based on the Message Passing Interface standard.The algorithm evenly distributes the response matrix sets among processors during the matrix formation process,thus enabling independent construction without communication.Once the formation tasks are completed,a collective operation merges and shares the matrix sets among the processors.For the solution process,the problem domain is decomposed into subdomains assigned to specific processors,and the red-black Gauss-Seidel iteration is employed within each subdomain to solve the response matrix equation.Point-to-point communication is conducted between adjacent subdomains to exchange data along the boundaries.The accuracy and efficiency of the parallel algorithm are verified using the KAIST and JRR-3 test cases.Numerical results obtained with multiple processors agree well with those obtained from Monte Carlo calculations.The parallelization of HVNM results in eigenvalue errors of 31 pcm/-90 pcm and fission rate RMS errors of 1.22%/0.66%,respectively,for the 3D KAIST problem and the 3D JRR-3 problem.In addition,the parallel algorithm significantly reduces computation time,with an efficiency of 68.51% using 36 processors in the KAIST problem and 77.14% using 144 processors in the JRR-3 problem.

关键词： Neutron transport Variational nodal method Parallelization KAIST JRR-3