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Non-B-form DNA is associated with centromere stability in newly-formed polyploid wheat

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Science China(Life Sciences) 2024年第7期67卷 1479-1488页

作者： Congyang Yi Qian Liu Yuhong huang Chang Liu Xianrui guo Chaolan Fan Kaibiao zhang Yang Liu Fangpu Han Institute of Genetics and Developmental Biology Chinese Academy of SciencesBeijing 100101China University of Chinese Academy of Sciences Beijing 100049China

Non-B-form DNA differs from the classic B-DNA double helix structure and plays a crucial regulatory role in replication and ***,the role of non-B-form DNA in centromeres,especially in polyploid wheat,remains ***,we systematically analyzed seven non-B-form DNA motif profiles(A-phased DNA repeat,direct repeat,G-quadruplex,inverted repeat,mirror repeat,short tandem repeat,and Z-DNA)in hexaploid *** found that three of these non-B-form DNA motifs were enriched at centromeric regions,especially at the CENH3-binding sites,suggesting that non-B-form DNA may create a favorable loading environment for the CENH3 *** investigate the dynamics of centromeric non-B form DNA during the alloploidization process,we analyzed DNA secondary structure using CENH3 ChIP-seq data from newly formed allotetraploid wheat and its two diploid *** found that newly formed allotetraploid wheat formed more non-B-form DNA in centromeric regions compared with their parents,suggesting that non-B-form DNA is related to the localization of the centromeric regions in newly formed ***,non-B-form DNA enriched in the centromeric regions was found to preferentially form on young LTR retrotransposons,explaining CENH3's tendency to bind to younger ***,our study describes the landscape of non-B-form DNA in the wheat genome,and sheds light on its potential role in the evolution of polyploid centromeres.

关键词： non-B-form DNA polyploid wheat centromere retrotransposon

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Hybrid vibration isolation optimization of a flexible manipulator based on neural network agent model

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Chinese Journal of Aeronautics 2024年第5期37卷 482-505页

作者： Yongxin zhang Liang LI Dingguo zhang Wei-Hsin LIAO Xian guo School of Science Nanjing University of Science and TechnologyNanjing 210094China Department of Mechanical and Automation Engineering The Chinese University of Hong KongHong KongChina

Segmented Active Constrained Layer Damping(SACLD)is an intelligent vibration-damping structure,which could be applied to the sectors of aviation,aerospace,and transportation engineering to reduce the vibration of flexible ***,machine learning technology is widely used in the engineering field because of its efficient multi-objective *** dynamic simulation of a rotational segmental flexible manipulator system is presented,in which enhanced active constrained layer damping is carried out,and the neural network model of Genetic Algorithm-Back Propagation(GA-BP)algorithm is *** suppression and structural optimization of the SACLD manipulator model are studied based on vibration mode and damping *** modal responses of the SACLD manipulator model at rest and rotation are *** addition,the four model indices are optimized using the GA-BP neural network:axial incision size,axial incision position,circumferential incision size,and circumferential incision ***,the best model for vibration suppression is obtained.

关键词： Machine learning Vibration suppression Flexible manipulator Segmented active constrained layer damping Structural optimization

An effective strategy of constructing multi-metallic oxides of ZnO/ CoNiO_(2)/CoO/C microflowers for improved supercapacitive performance

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Chinese Journal of Chemical Engineering 2024年第3期67卷 1-8页

作者： Wei guo Yan zhang Xiaxin Lei Shuang Wang College of Physics Taiyuan University of TechnologyJinzhong 030600China College of Environmental Science and Engineering Taiyuan University of TechnologyJinzhong 030600China Shanxi Key Laboratory of Gas Energy Efficient and Clean Utilization Taiyuan University of TechnologyTaiyuan 030024China

In this work,a new ZnO/CoNiO_(2)/CoO/C metal oxides composite is prepared by cost-effective hydrothermal method coupled with annealing process under N_(2) ***,the oxidation-defect annealing environment is conducive to both morphology and component of the composite,which flower-like ZnO/CoNiO_(2)/CoO/C is *** from good chemical stability of ZnO,high energy capacity of CoNiO_(2) and CoO and good conductivity of C,the as-prepared sample shows promising electrochemical behavior,including the specific capacity of 1435 C·g^(-1) at 1 A·g^(-1),capacity retention of 87.3%at 20 A·g^(-1),and cycling stability of 90.5%for 3000 cycles at 5 A·g^(-1),***,the prepared ZnO/CoNiO_(2)/CoO/C/NF//AC aqueous hybrid supercapacitors device delivers the best specific energy of 55.9 W·h·kg^(-1) at 850 W·kg^(-1).The results reflect that the as-prepared ZnO/CoNiO_(2)/CoO/C microflowers are considered as high performance electrode materials for supercapacitor,and the strategy mentioned in this paper is benefit to prepare mixed metal oxides composite for energy conversion and storage.

关键词： Composites Electrochemistry Hydrothermal Transition metal oxides Structural control Supercapacitors

NeurstrucEnergy:A bi-directional GNN model for energy prediction of neural networks in IoT

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Digital Communications and Networks 2024年第2期10卷 439-449页

作者： Chaopeng guo Zhaojin Zhong Zexin zhang Jie Song Software Campus Northeastern UniversityShenyang110000LiaoningChina

A significant demand rises for energy-efficient deep neural networks to support power-limited embedding devices with successful deep learning applications in IoT and edge computing *** accurate energy prediction approach is critical to provide measurement and lead optimization ***,the current energy prediction approaches lack accuracy and generalization ability due to the lack of research on the neural network structure and the excessive reliance on customized training *** paper presents a novel energy prediction model,*** treats neural networks as directed graphs and applies a bi-directional graph neural network training on a randomly generated dataset to extract structural features for energy *** has advantages over linear approaches because the bi-directional graph neural network collects structural features from each layer's parents and *** results show that NeurstrucEnergy establishes state-of-the-art results with mean absolute percentage error of 2.60%.We also evaluate NeurstrucEnergy in a randomly generated dataset,achieving the mean absolute percentage error of 4.83%over 10 typical convolutional neural networks in recent years and 7 efficient convolutional neural networks created by neural architecture *** code is available at https://***/NEUSoftGreenAI/***.

关键词： Internet of things Neural network energy prediction Graph neural networks Graph structure embedding Multi-head attention

Hierarchical Spinning of Janus Textiles with Anisotropic Wettability for Wound Healing

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Research 2024年第1期2023卷 97-105页

作者： Han zhang Lingyu Sun Jiahui guo Yuanjin Zhao Department of Rheumatology and Immunology Nanjing Drum Tower HospitalSchool of Biological Science and Medical EngineeringSoutheast UniversityNanjingJiangsu 210096China Oujiang Laboratory(Zhejiang Lab for Regenerative Medicine Vision and Brain Health)Wenzhou InstituteUniversity of Chinese Academy of SciencesWenzhouZhejiang 325001China

Wound healing and tissue repair are recognized as basic human health problems *** to accelerate the reparative process are focused on developing functional wound ***,we present novel Janus textiles with anisotropic wettability from hierarchical microfluidic spinning for wound *** hydrophilic hydrogel microfibers from microfluidics are woven into textiles for freeze-drying treatment,followed by the deposition of electrostatic spinning nanofibers composed of hydrophobic polylactic acid(PLA)and silver *** electrospun nanofiber layer can be well coupled with the hydrogel microfiber layer to generate Janus textiles with anisotropic wettability due to the roughness of the hydrogel textile surface and the incomplete evaporation of PLA solution when reaching the *** wound treatment with the hydrophobic PLA side contacting the wound surface,the wound exudate can be pumped from the hydrophobic to the hydrophilic side based on the wettability differential derived drainage *** this process,the hydrophobic side of the Janus textile can prevent excess fluid from infiltrating the wound again,preventing excessive moisture and preserving the breathability of the *** addition,the silver nanoparticles contained in the hydrophobic nanofibers could impart the textiles with good antibacterial effect,which further promote the wound healing *** features indicate that the described Janus fiber textile has great application potential in the field of wound treatment.

关键词： silver spinning healing

Novel data-driven sparse polynomial chaos and analysis of covariance for aerodynamics of compressor cascades with dependent geometric uncertainties

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Chinese Journal of Aeronautics 2024年第6期37卷 89-108页

作者： Zhengtao guo Wuli CHU Haoguang zhang Tianyuan JI School of Power and Energy Northwestern Polytechnical UniversityXi’an 710072China

Polynomial Chaos Expansion(PCE)has gained significant popularity among engineers across various engineering disciplines for uncertainty ***,traditional PCE suffers from two major ***,the orthogonality of polynomial basis functions holds only for independent input variables,limiting the model’s ability to propagate uncertainty in dependent ***,PCE encounters the"curse of dimensionality"due to the high computational cost of training the model with numerous polynomial *** practical manufacturing,compressor blades are subject to machining precision limitations,leading to deviations from their ideal geometric *** deviations require a large number of geometric parameters to describe,and exhibit significant *** efficiently quantify the impact of high-dimensional dependent geometric deviations on the aerodynamic performance of compressor blades,this paper firstly introduces a novel approach called Data-driven Sparse PCE(DSPCE).The proposed method addresses the aforementioned challenges by employing a decorrelation algorithm to directly create multivariate basis functions,accommodating both independent and dependent random ***,the method utilizes an iterative Diffeomorphic Modulation under Observable Response Preserving Homotopy regression algorithm to solve the unknown coefficients,achieving model sparsity while maintaining fitting ***,the study investigates the simultaneous effects of seven dependent geometric deviations on the aerodynamics of a high subsonic compressor cascade by using the DSPCE method proposed and sensitivity analysis of *** joint distribution of the dependent geometric deviations is determined using Quantile-Quantile plots and normal copula functions based on finite measurement *** results demonstrate that the correlations between geometric deviations significantly impact the variance of aerodynamic performance and the flow ***,

关键词： Data-driven sparse polyno-mial chaos Analysis of covariance Dependent uncertainty Aerodynamic performance Compressor cascade

Recent progress on copper catalysts with different surface states for CO_(2)electroreduction

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Journal of Energy Chemistry 2024年第1期88卷 10-27,I0001页

作者： Wenjun zhang Yang Yang Donggang guo Lu Liu Tianjin Key Laboratory of Environmental Remediation and Pollution Control College of Environmental Science and EngineeringNankai UniversityTianjin 300350China Shanxi Laboratory for Yellow River College of Environment and ResourceShanxi UniversityTaiyuan 030006ShanxiChina

The electrochemical carbon dioxide reduction reaction(eCO_(2)RR),which converts CO_(2)into various hydrocarbons or alcohols,has been extensively researched because it promises a sustainable energy ***,only copper(Cu)can currently achieve stable and efficient hydrocarbon conversion in the eCO_(2)***,understanding the catalytic mechanisms and summarizing the research progress on synthesis strategies of Cu catalysts are essential for the eCO_(2)*** paper reviews Cu catalysts with different surface states of Cu catalysts:oxide-derived Cu,Cu nanoparticles,Cu single atoms,and Cu *** then reviews the development and progress of different Cu-catalyst preparation methods in recent years,focusing on the activity and selectivity of *** revealing the tendencies of catalytic selection and deep reactive mechanisms of Cu catalysts with four different surface states,this review can guide the subsequent construction of catalysts and provides an understanding of catalytic mechanisms.

关键词： eCO_(2)RR Oxide-derived Cu Cu nanoparticles Cu single atoms Cu nanoclusters

Hierarchical Task Planning for Power Line Flow Regulation

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CSEE Journal of Power and Energy Systems 2024年第1期10卷 29-40页

作者： Chenxi Wang Youtian Du Yanhao huang Yuanlin Chang Zihao guo the Ministry of Education Key Lab for Intelligent Networks and Network Security Xi'an Jiaotong UniversityXi'an 713599China the State Key Laboratory of Power Grid Safety and Energy Conservation China Electric Power Research InstituteBeijing 100192China

The complexity and uncertainty in power systems cause great challenges to controlling power *** a popular data-driven technique,deep reinforcement learning(DRL)attracts attention in the control of power ***,DRL has some inherent drawbacks in terms of data efficiency and *** paper presents a novel hierarchical task planning(HTP)approach,bridging planning and DRL,to the task of power line flow ***,we introduce a threelevel task hierarchy to model the task and model the sequence of task units on each level as a task planning-Markov decision processes(TP-MDPs).Second,we model the task as a sequential decision-making problem and introduce a higher planner and a lower planner in HTP to handle different levels of task *** addition,we introduce a two-layer knowledge graph that can update dynamically during the planning procedure to assist *** results conducted on the IEEE 118-bus and IEEE 300-bus systems demonstrate our HTP approach outperforms proximal policy optimization,a state-of-the-art deep reinforcement learning(DRL)approach,improving efficiency by 26.16%and 6.86%on both systems.

关键词： Knowledge graph power line flow regulation reinforcement learning task planning

A LiDAR Point Clouds Dataset of Ships in a Maritime Environment

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IEEE/CAA Journal of Automatica Sinica 2024年第7期11卷 1681-1694页

作者： Qiuyu zhang Lipeng Wang Hao Meng Wen zhang Genghua huang the College of Intelligent Systems Science and Engineering Harbin Engineering UniversityHarbin 150001China Key Laboratory of Space Active Opto-Electronics Technology Shanghai Institute of Technical PhysicsChinese Academy of SciencesShanghai 200083China

For the first time, this article introduces a LiDAR Point Clouds Dataset of Ships composed of both collected and simulated data to address the scarcity of LiDAR data in maritime applications. The collected data are acquired using specialized maritime LiDAR sensors in both inland waterways and wide-open ocean environments. The simulated data is generated by placing a ship in the LiDAR coordinate system and scanning it with a redeveloped Blensor that emulates the operation of a LiDAR sensor equipped with various laser beams. Furthermore,we also render point clouds for foggy and rainy weather conditions. To describe a realistic shipping environment, a dynamic tail wave is modeled by iterating the wave elevation of each point in a time series. Finally, networks serving small objects are migrated to ship applications by feeding our dataset. The positive effect of simulated data is described in object detection experiments, and the negative impact of tail waves as noise is verified in single-object tracking experiments. The Dataset is available at https://***/zqy411470859/ship_dataset.

关键词： 3D point clouds dataset dynamic tail wave fog simulation rainy simulation simulated data