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Evolutionary mechanisms and practical significance of reproductive success and clonal diversity in unisexual vertebrate polyploids

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Science China(Life Sciences) 2024年第3期67卷 449-459页

作者： Meng Lu Li zhou Jian-Fang gui State Key Laboratory of Freshwater Ecology and Biotechnology Hubei Hongshan Laboratorythe Innovation Academy of Seed DesignInstitute of HydrobiologyChinese Academy of SciencesWuhan 430072China University of Chinese Academy of Sciences Beijing 100049China

Unisexual reproduction is generally relevant to polyploidy, and unisexual vertebrates are often considered an evolutionary “dead end” due to the accumulation of deleterious mutations and absence of genetic diversity. However, some unisexual polyploids have developed strategies to avoid genomic decay, and thus provide ideal models to unveil unexplored evolutionary mechanisms, from the reproductive success to clonal diversity creation. This article reviews the evolutionary mechanisms for overcoming meiotic barrier and generating genetic diversity in unisexual vertebrates, and summarizes recent research advancements in the polyploid Carassius complex. Gynogenetic gibel carp(Carassius gibelio) is a unique amphitriploid that has undergone a recurrent autotriploidy and has overcome the bottleneck of triploid sterility via gynogenesis. Recently, an efficient strategy in which ploidy changes, including from amphitriploid to amphitetraploid, then from amphitetraploid to novel amphitriploid, drive unisexual-sexual-unisexual reproduction transition and clonal diversity has been *** on this new discovery, multigenomic reconstruction biotechnology has been used to breed a novel strain with superior growth and stronger disease resistance. Moreover, a unique reproduction mode that combines both abilities of ameiotic oogenesis and sperm-egg fusion,termed as ameio-fusiongensis, has been discovered, and it provides an efficient approach to synthesize sterile allopolyploids. In order to avoid ecological risks upon escape and protect the sustainable property rights of the aquaculture seed industry, a controllable fertility biotechnology approach for precise breeding is being developed by integrating sterile allopolyploid synthesis and gene-editing *** review provides novel insights into the origin and evolution of unisexual vertebrates and into the attempts being made to exploit new breeding biotechnologies in aquaculture.

关键词： unisexual vertebrates polyploidy reproduction transition clonal diversity precise breeding genomic reconstruction controllable fertility

Generation of input spectrum for electrolysis stack degradation test applied to wind power PEM hydrogen production

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Global Energy Interconnection 2024年第4期7卷 462-474页

作者： Yanhui xu Guanlin Li Yuyuan gui Zhengmao Li School of Electrical and Electronic Engineering North China Electric Power UniversityBeijing 102206P.R.China School of Electrical Engineering Aalto UniversityFinland

Hydrogen production by proton exchange membrane electrolysis has good fluctuation adaptability,making it suitable for hydrogen production by electrolysis in fluctuating power sources such as wind ***,current research on the durability of proton exchange membrane electrolyzers is *** the typical operating conditions of wind power electrolysis for hydrogen production can provide boundary conditions for performance and degradation tests of electrolysis *** this study,the operating condition spectrum of an electrolysis stack degradation test cycle was *** on the rate of change of the wind farm output power and the time-averaged peak-valley difference,a fluctuation output power sample set was *** characteristic quantities that played an important role in the degradation of the electrolysis stack were *** reduction of the operating data was performed using principal component *** analysis of the data segments was completed using an improved Gaussian mixture clustering *** the annual output power data of wind farms in Northwest China with a sampling rate of 1 min as an example,the cyclic operating condition spectrum of the proton-exchange membrane electrolysis stack degradation test was *** preliminary simulation analysis,the typical operating condition proposed in this paper effectively reflects the impact of the original curve on the performance degradation of the electrolysis *** study provides a method for evaluating the degradation characteristics and system efficiency of an electrolysis stack due to fluctuations in renewable energy.

关键词： Hydrogen production by electrolysis of water Wind power Proton exchange membrane electrolyzer Gaussian mixture model Cyclic operating condition

A Deep Residual PLS for Data-Driven Quality Prediction Modeling in Industrial Process

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IEEE/CAA Journal of Automatica Sinica 2024年第8期11卷 1777-1785页

作者： Xiaofeng Yuan Weiwei xu Yalin Wang Chunhua Yang Weihua gui School of Automation Central South UniversityChangsha 410083China She is now with Guangzhou Electromechanical Technician College Guangzhou 510000China

Partial least squares(PLS)model is the most typical data-driven method for quality-related industrial tasks like soft ***,only linear relations are captured between the input and output data in the *** is difficult to obtain the remaining nonlinear information in the residual subspaces,which may deteriorate the prediction performance in complex industrial *** fully utilize data information in PLS residual subspaces,a deep residual PLS(DRPLS)framework is proposed for quality prediction in this *** by deep learning,DRPLS is designed by stacking a number of PLSs successively,in which the input residuals of the previous PLS are used as the layer *** enhance representation,nonlinear function is applied to the input residuals before using them for stacking highlevel *** each PLS,the output parts are just the output residuals from its previous ***,the output prediction is obtained by adding the results of each *** effectiveness of the proposed DRPLS is validated on an industrial hydrocracking process.

关键词： Deep residual partial least squares(DRPLS) nonlinear function quality prediction soft sensor

Screening biomarkers for spinal cord injury using weighted gene co-expression network analysis and machine learning

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Neural Regeneration Research 2024年第12期19卷 2723-2734页

作者： Xiaolu Li Ye Yang Senming xu Yuchang gui Jianmin Chen Jianwen xu Department of Rehabilitation Medicine The First Affiliated Hospital of Guangxi Medical UniversityNanningGuangxi Zhuang Autonomous RegionChina Department of Rehabilitation Medicine Guilin People’s HospitalGuilinGuangxi Zhuang Autonomous RegionChina Department of Rehabilitation Medicine The First Affiliated Hospital of Fujian Medical UniversityFuzhouFujian ProvinceChina

Immune changes and inflammatory responses have been identified as central events in the pathological process of spinal co rd *** can greatly affect nerve regeneration and functional ***,there is still limited understanding of the peripheral immune inflammato ry response in spinal cord inju *** this *** obtained microRNA expression profiles from the peripheral blood of patients with spinal co rd injury using high-throughput *** also obtained the mRNA expression profile of spinal cord injury patients from the Gene Expression Omnibus(GEO)database(GSE151371).We identified 54 differentially expressed microRNAs and 1656 diffe rentially expressed genes using bioinformatics *** enrichment analysis revealed that various common immune and inflammation-related signaling pathways,such as neutrophil extracellular trap formation pathway,T cell receptor signaling pathway,and nuclear factor-κB signal pathway,we re abnormally activated or inhibited in spinal cord inju ry patient *** applied an integrated strategy that combines weighted gene co-expression network analysis,LASSO logistic regression,and SVM-RFE algorithm and identified three biomarke rs associated with spinal cord injury:ANO10,BST1,and *** verified the expression levels and diagnostic perfo rmance of these three genes in the original training dataset and clinical samples through the receiver operating characteristic *** polymerase chain reaction results showed that ANO20 and BST1 mRNA levels were increased and ZFP36L2 mRNA was decreased in the peripheral blood of spinal cord injury *** also constructed a small RNA-mRNA interaction network using ***,we evaluated the proportion of 22 types of immune cells in the peripheral blood of spinal co rd injury patients using the CIBERSORT *** proportions of naive B cells,plasma cells,monocytes,and neutrophils were increased while the proportions of memory B cells,C

关键词： bioinformatics analysis biomarker CIBERSORT GEO dataset LASSO miRNA-mRNA network RNA sequencing spinal cord injury SVM-RFE weighted gene co-expression network analysis

Towards the insights into the deactivation behavior of acetylene hydrogenation catalyst

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Petroleum Science 2024年第2期21卷 1405-1414页

作者： Hai-Xia Su Yang Jiao Jian-Gong Shi Zhi-Wei Yuan Di Zhang xu-Peng Wang Jing Ren Dan Liu Jian-zhou gui Hai-Yang Gao Xiao-Li xu State Key Laboratory of Separation Membranes&Membrane Processes Tianjin Key Laboratory of Green Chemical Technology and Process EngineeringSchool of Material Science and EngineeringTiangong UniversityTianjin300387China Institute of Engineering Technology Sinopec Catalyst Co.LtdBeijing101100China State Key Laboratory of Separation Membranes and Membrane Processes Tianjin Key Laboratory of Green Chemical Technology and Process EngineeringSchool of ChemistryTiangong UniversityTianjin300387China

A series of model catalysts were obtained by treating commercial fresh and spent catalysts unloaded from the factory with different methods, including green oil dipping, extraction and high-temperature regeneration;finally, the deactivation behavior of the commercial catalyst for acetylene hydrogenation were studied. The influence of various possible deactivation factors on the catalytic performance was elucidated via detailed structural characterization, surface composition analysis, and activity *** results showed that green oil, carbon deposit and sintering of active metal were the main reasons for deactivation, among which green oil and carbon deposit led to rapid deactivation, while the activity could be recovered after regeneration by high-temperature calcination. The sintering of active metal components was attributed to the high-temperature regeneration in hydrothermal conditions, which was slow but irreversible and accounted for permanent deactivation. Thus, optimizing the regeneration is expected to extend the service life of the commercial catalyst.

关键词： Acetylene Hydrogenation Green oil Carbon deposit Sintering Catalyst deactivation

Inverse aerodynamic design for distributed propulsion wing with expected circulation distribution

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CHINESE JOURNAL OF AERONAUTICS 2024年第9期37卷 206-223页

作者： Sun, Pengbo zhou, zhou Li, xu Wang, Kelei Northwestern Polytech Univ Sch Aeronaut Xian 710072 Peoples R China

Distributed Propulsion Wing (DPW) technology offers significant advantages in terms of flight energy savings, but the strong aerodynamic coupling between the propulsive internal flow and aerodynamic external flow brings significant design challenges. As the primary DPW profile design is of great significance, this paper proposes a hybrid method to solve the inverse problem mainly based on the formula relationship between the required aerodynamic loads and the profile shape, which is more direct and instructive compared with traditional parametric iterative methods. The aerodynamic characteristics are described by the circulation distribution in the Fourier series form, then the mean camber line of the profile is solved through the re-derived airfoil theory considering disk's influence. Further CFD correction methods are also proposed. To validate the effectiveness and feasibility of the proposed hybrid inverse method, several DPW profile design tests are then conducted. Finally, the relationship between 2D and realistic 3D unit shape is also researched. The results show that the proposed inverse design method has great accuracy and convergence speed in the design tests, and shows good robustness against changes of the design parameters. The 2D profile shape and the actual 3D shape of DPW unit can establish an aerodynamicpropulsion equivalent relationship based on the same internal mass fluxes. (c) 2024 Production and hosting by Elsevier Ltd. on behalf of Chinese Society of Aeronautics and Astronautics. This is an open access article under the CC BY-NC-ND license (http://***/ licenses/by-nc-nd/4.0/).

关键词： Inverse problem Aerodynamic load Fourier series Flux FLOW SIMULATION SHAPE DESIGN HYBRID OPTIMIZATION

Resource Allocation for Channel Estimation in Reconfigurable Intelligent Surface-Aided Multi-Cell Networks

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Journal of Communications and Information Networks 2024年第1期9卷 64-79页

作者： Yining xu Sheng zhou Department of Electronic Engineering Beijing National Research Center for Information Science and TechnologyTsinghua UniversityBeijing 100084China

Reconfigurable intelligent surface(RIS)is a promising solution to deal with the blockage-sensitivity of millimeter wave band and reduce the high energy consumption caused by network densification. However, deploying large scale RISs may not bring expected performance gain due to significant channel estimation overhead and non-negligible reflected *** this paper,we derive the analytical expressions of the coverage probability, area spectrum efficiency(ASE)and energy efficiency (EE)of a downlink RIS-aided multi-cell *** order to optimize the network performance, we investigate the conditions for the optimal number of training symbols of each antenna-to-antenna and antenna-to-element path (referred to as the optimal unit training overhead) in channel *** study shows that:1)RIS deployment is not“the more, the better”, only when blockage objects are dense should one deploy more RISs;2) the coverage probability is maximized when the unit training overhead is designed as large as possible;3)however,the ASE-and-EE-optimal unit training overhead exists. It is a monotonically increasing function of the frame length and a monotonically decreasing function of the average signal-to-noise-ratio (in the high signal-to-noise-ratio region). Additionally,the optimal unit training overhead is smaller when communication nodes deploy particularly few or many antennas.

关键词： reconfigurable intelligent surface multi-cell network directional transmissions channel estimation resource allocation stochastic geometry

Bayesian inference of neutron-skin thickness and neutron-star observables based on effective nuclear interactions

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Science China(Physics,Mechanics & Astronomy) 2024年第8期67卷 97-105页

作者： Jia zhou Jun xu Shanghai Institute of Applied Physics Chinese Academy of SciencesShanghai 201800China University of Chinese Academy of Sciences Beijing 100049China School of Physics Science and Engineering Tongji UniversityShanghai 200092China

We have obtained the constraints on the density dependence of the symmetry energy from neutron-skin thickness data by parityviolating electron scatterings and neutron-star observables using a Bayesian approach,based on the standard Skyrme-HartreeFock(SHF)model and its extension as well as the relativistic mean-field(RMF)*** the neutron-skin thickness data(neutron-star observables)mostly constrain the symmetry energy at subsaturation(suprasaturation)densities,they may more or less constrain the behavior of the symmetry energy at suprasaturation(subsaturation)densities,depending on the energy-density functional *** showing the final posterior density dependence of the symmetry energy,we also compare the slope parameters of the symmetry energy at 0.10 fm-3as well as the values of the symmetry energy at twice saturation density from three effective nuclear *** present work serves as a comparison study based on relativistic and non-relativistic energy-density functionals,for constraining the nuclear symmetry energy from low to high densities using a Bayesian approach.

关键词： symmetry energy neutron skin neutron star

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A hybrid physics-informed data-driven neural network for CO_(2) storage in depleted shale reservoirs

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Petroleum Science 2024年第1期21卷 286-301页

作者： Yan-Wei Wang Zhen-xue Dai gui-Sheng Wang Li Chen Yu-zhou Xia Yu-Hao zhou College of Construction Engineering Jilin UniversityChangchun130026JilinChina Institute of Intelligent Simulation and Early Warning for Subsurface Environment Jilin UniversityChangchun130026JilinChina School of Energy Resources China University of GeosciencesBeijing100083China Department of Safety Environmental Protection and Quality ManagementShengli OilfieldSinopecDongying257000ShandongChina Key Laboratory of Thermo-Fluid Science and Engineering of MOE School of Energy and Power EngineeringXi'an Jiaotong UniversityXi'an710049ShaanxiChina College of Computer Science and Technology China University of Petroleum(East China)Qingdao266580ShandongChina Department of Physics University of FribourgFribourg1700Switzerland

To reduce CO_(2) emissions in response to global climate change,shale reservoirs could be ideal candidates for long-term carbon geo-sequestration involving multi-scale transport ***,most current CO_(2) sequestration models do not adequately consider multiple transport ***,the evaluation of CO_(2) storage processes usually involves laborious and time-consuming numerical simulations unsuitable for practical prediction and *** this paper,an integrated model involving gas diffusion,adsorption,dissolution,slip flow,and Darcy flow is proposed to accurately characterize CO_(2) storage in depleted shale reservoirs,supporting the establishment of a training *** this basis,a hybrid physics-informed data-driven neural network(HPDNN)is developed as a deep learning surrogate for prediction and *** incorporating multiple sources of scientific knowledge,the HPDNN can be configured with limited simulation resources,significantly accelerating the forward and inversion ***,the HPDNN can more intelligently predict injection performance,precisely perform reservoir parameter inversion,and reasonably evaluate the CO_(2) storage capacity under complicated *** validation and test results demonstrate that the HPDNN can ensure high accuracy and strong robustness across an extensive applicability range when dealing with field data with multiple noise *** study has tremendous potential to replace traditional modeling tools for predicting and making decisions about CO_(2) storage projects in depleted shale reservoirs.

关键词： Deep learning Physics-informed data-driven neural network Depleted shale reservoirs CO_(2)storage Transport mechanisms