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Genome-wide binding analysis of transcription factor Rice Indeterminate 1 reveals a complex network controlling rice floral transition

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Journal of Integrative Plant Biology 2022年第9期64卷 1690-1705页

作者： Shuo zhang Li Deng Lun zhao Changyin wu National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research(wuhan) Hubei Hongshan LaboratoryHuazhong Agricultural UniversityWuhan430070 China

RICE INDETERMINATE 1(RID1)plays a critical role in controlling floral transition in rice(Oryza sativa).However,the molecular basis for this effect,particularly the target genes and regulatory specificity,remains largely unclear.Here,we performed chromatin immunoprecipitation followed by sequencing(ChIP-seq)in young leaves at the pre-floral-transition stage to identify the target genes of RID1,identifying 2,680 genes associated with RID1 binding sites genome-wide.RID1 binding peaks were highly enriched for TTTGTC,the direct binding motif of the INDETERMINATE DOMAIN protein family that includes RID1.Interestingly,CACGTG and GTGGGCCC,two previously uncharacterized indirect binding motifs,were enriched through the interactions of RID1 with the novel floweringpromoting proteins OsPIL12 and OsTCP11,respectively.Moreover,the ChIP-seq data demonstrated that RID1 bound to numerous rice heading-date genes,such as HEADING DATE1(HD1)and FLAVIN-BINDING,KELCH REPEAT,F-BOX 1(OsFKF1).Notably,transcriptome sequencing(RNA-seq)analysis revealed roles of RID1 in diverse developmental pathways.Genetic analysis combined with genome-wide ChIP-seq and RNA-seq results showed that RID1 directly binds to the promoter of OsERF#136(a repressor of rice flowering)and negatively regulates its expression.Overall,our findings provide new insights into the molecular and genetic mechanisms underlying rice floral transition and characterize OsERF#136 as a previously unrecognized direct target of RID1.

关键词： ChIP-seq floral transition OsERF#136 rice(Oryza sativa) RID1 RNA-seq

Effect of Al_(2)O_(3) content on the viscosity and structure of CaO-SiO_(2)-Cr_(2)O_(3)-Al_(2)O_(3) slags

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International Journal of Minerals,Metallurgy and Materials 2022年第8期29卷 1522-1531页

作者： Fang Yuan Zheng zhao Yanling zhang Tuo wu State Key Laboratory of Advanced Metallurgy University of Science and Technology BeijingBeijing 100083China

The effect of Al_(2)O_(3) content on the viscosity and structure of CaO-SiO_(2)-Cr_(2)O_(3)Al_(2)O_(3) slags was investigated to facilitate recycling of Cr in steelmaking slags.The slags exhibit good Newtonian behavior at high temperature.The viscosity of acidic slag first increases from 0.825 to 1.141 Pa·s as the Al_(2)O_(3) content increases from 0 to 10wt%and then decreases to 1.071 Pa·s as the Al_(2)O_(3) content increases further to 15wt%.The viscosity of basic slag first increases from 0.084 to 0.158 Pa·s as the Al_(2)O_(3) content increases from 0 to 15wt%and then decreases to 0.135 Pa·s as the Al_(2)O_(3) content increases further to 20wt%.Furthermore,Cr_(2)O_(3)containing slag requires less Al_(2)O_(3) to reach the maximum viscosity than Cr_(2)O_(3)free slag;the Al_(2)O_(3) contents at which the behavior changes are 10wt%and 15wt%for acidic and basic slags,respectively.The ac-tivation energy of the slags is consistent with the viscosity results.Raman spectra demonstrate that[AlO_(4)]tetrahedra appear initially and were replaced by[AlO_(6)]octahedra with further addition of Al_(2)O_(3).The dissolved organic phosphorus content of the slag first increases and then de-creases with increasing Al_(2)O_(3) content,which is consistent with the viscosity and Raman results.

关键词： viscosity structure Cr-containing slag Raman spectra

Enthalpy-change driven synthesis of high-entropy perovskite nanoparticles

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Nano Research 2022年第6期15卷 4867-4872页

作者： Siyang Nie Liang wu Lingci zhao Pengfei zhang School of Chemistry and Chemical Engineering Shanghai Jiao Tong UniversityShanghai 200240China

Due to their diverse and tunable composition,distorted lattice and excellent stability,high-entropy ceramics(HECs)hold great promise for catalysis,especially when they present as nanoparticles(NPs).However,current HECs are typically limited to bulky materials with none or fewer defects,because high synthetic temperature(e.g.,1,000–1,200°C)is usually required to highlight the entropic contribution(TΔS)inΔG=ΔH−TΔS.Being different with previous strategies,a negative Gibbs free energy for HECs crystallization is obtained by dramatically decreasing the mixing enthalpy(ΔH).Guided by this principle,single-phase highentropy La(Ni_(0.2)Mn_(0.2)Cu_(0.2)Fe_(0.2)Co_(0.2))O_(3−δ)perovskite(HE-LMO)NPs were prepared at a relatively low temperature(≤500°C).Interestingly,abundant oxygen vacancies were directly created within HE-LMO NPs,which exhibited good activity in catalytic oxidation.Meanwhile,the high-entropy structure endows as-made HE-LMO with robust stability even with 5 vol.%water in feeding gas.Density functional theory(DFT)calculations revealed that the defective sites in HE-LMO NPs facilitated the charge transfer from HE-LMO to CO,thus activating the adsorbed CO gas.The current work may inspire future design and synthesis of HECs NPs.

关键词： enthalpy-change high-entropy ceramics mechanochemical synthesis perovskite CO oxidation

Stochastic dynamic simulation of railway vehicles collision using data-driven modelling approach

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Railway Engineering Science 2022年第4期30卷 512-531页

作者： ShaodiDong zhao Tang Michelle wu Jianjun zhang State Key Laboratory of Traction Power Southwest Jiaotong UniversityChengdu 610031China National Centre for Computer Animation Bournemouth UniversityDorsetUK

Using stochastic dynamic simulation for railway vehicle collision still faces many challenges,such as high modelling complexity and time-consuming.To address the challenges,we introduce a novel data-driven stochastic process modelling(DSPM)approach into dynamic simulation of the railway vehicle collision.This DSPM approach consists of two steps:(i)process description,four kinds of kernels are used to describe the uncertainty inherent in collision processes;(ii)solving,stochastic variational inferences and mini-batch algorithms can then be used to accelerate computations of stochastic processes.By applying DSPM,Gaussian process regression(GPR)and finite element(FE)methods to two collision scenarios(i.***.lead car colliding with a rigid wall,and the lead car colliding with another lead car),we are able to achieve a comprehensive analysis.The comparison between the DSPM approach and the FE method revealed that the DSPM approach is capable of calculating the corresponding confidence interval,simultaneously improving the overall computational efficiency.Comparing the DSPM approach with the GPR method indicates that the DSPM approach has the ability to accurately describe the dynamic response under unknown conditions.Overall,this research demonstrates the feasibility and usability of the proposed DSPM approach for stochastic dynamics simulation of the railway vehicle collision.

关键词： Dynamic simulation Railway vehicle collision Stochastic process Data-driven stochastic process modelling

D-Shaped Tellurite Photonic Crystal Fiber Hydrogen and Methane Sensor Based on Four-Wave Mixing With SPR Effect

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Photonic Sensors 2023年第1期13卷 25-39页

作者： Hai LIU Bo wu Cong CHEN Benlei zhao Xu zhang Hancheng zhang School of Information and Control Engineering China University of Mining and TechnologyXuzhou 221116China Engineering Research Center of Intelligent Control for Underground Space(Ministry of Education) China University of Mining and TechnologyXuzhou 221116China

A new D-shaped tellurite photonic crystal fiber sensor based on the four-wave mixing(FWM)effect with the surface plasmon resonance(SPR)effect is designed and optimized.The substrate of the D-shaped photonic crystal fiber(D-PCF)is tellurite glass,and the polished surface is plated with the gold film and hydrogen gas-sensitive film.An air hole of the inner cladding,which is plated with the gold film and methane gas-sensitive film,is selected as the second sensing channel to simultaneously measure the concentration of hydrogen and methane.Based on the four-wave mixing,the wavelength shifts of the Stokes and anti-Stokes spectra resulting from the variation of the gas concentration can be used to accurately detect the concentrations of methane and hydrogen.Meanwhile,it is found that the SPR effect can increase the wavelength shifts,which means the sensitivity of methane and hydrogen augment.After parameter optimization,the maximum sensitivities of methane and hydrogen are 4.03 nm/%and-14.19 nm/%,respectively.Both the linearities are up to 99.9%.The resolution of methane is 1.25×10^(-2)%and hydrogen is 7.14×10^(-3)%.Moreover,the fiber length of this sensor is only 20mm,which is conducive to the construction of a compact or ultra-compact embedded FWM fiber sensor.

关键词： Four-wave mixing surface plasmon resonance D-shaped photonic crystal fiber gas sensing

Classification of birds and drones by exploiting periodical motions in Doppler spectrum series

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Journal of Systems Engineering and Electronics 2023年第1期34卷 19-27页

作者： DUAN Jia zhang Lei wu Yifeng zhang Yue zhao Zeya GUO Xinrong School of Electronics and Communication Sun Yat-Sen UniversityShenzhen 518107China Beijing Institute of Tracking and Telecommunication Technology Beijing 100854China Armed Police Engineering University Xi’an 510507China

With the rapidly growing abuse of drones, monitoring and classification of birds and drones have become a crucial safety issue. With similar low radar cross sections(RCSs), velocities, and heights, drones are usually difficult to be distinguished from birds in radar measurements. In this paper, we propose to exploit different periodical motions of birds and drones from highresolution Doppler spectrum sequences(DSSs) for classification.This paper presents an elaborate feature vector representing the periodic fluctuations of RCS and micro kinematics. Fed by the Doppler spectrum and feature sequence, the long to short-time memory(LSTM) is used to solve the time series classification.Different classification schemes to exploit the Doppler spectrum series are validated and compared by extensive real-data experiments, which confirms the effectiveness and superiorities of the proposed algorithm.

关键词： target classification long-to-short memory(LSTM) drone discrimination Doppler spectrum series

Bismuth chloride@mesocellular carbon foam nanocomposite cathode materials for rechargeable chloride ion batteries

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Chinese Chemical Letters 2022年第4期33卷 2200-2204页

作者： Chang zhang Shijiao Sun Meifen wu Xiangyu zhao College of Materials Science and Engineering Nanjing Tech UniversityNanjing 211816China CAS Key Laboratory of Materials for Energy Conversion Shanghai Institute of CeramicsChinese Academy of SciencesShanghai 200050China Jiangsu Collaborative Innovation Center for Advanced Inorganic Functional Composites Nanjing Tech UniversityNanjing 211816China

Chloride ion batteries(CIB) are considered to be one of the most promising energy storage devices. As cathode materials for CIBs, metal chlorides have many advantages, such as high theoretical energy density, abundant elemental resources and ideal discharge voltage plateau. However, the dissolution and huge volume change of metal chlorides during cycling lead to considerable short lifespan, which limits their potential application for CIBs. Herein, the bismuth chloride nanocrystal is confined in mesocellular carbon foam matrix by a new vacuum impregnation approach. The mesocellular carbon foam with large interconnected pores(15.7 or 23.2 nm) may buffer the large volume variation of bismuth chloride during charge and discharge, giving rise to significantly enhanced electrochemical performance. The as-prepared bismuth chloride@mesocellular carbon foam cathode delivered an initial discharge capacity of 298 m Ah/g and a reversible capacity of 91 m Ah/g after 60 cycles. In contrast, the pure bismuth chloride cathode almost cannot discharge after 30 cycles. This is the first report that the metal chloride cathode can achieve a prolonged cycling in CIBs.

关键词： Chloride ion batteries Cathode materials Bismuth chloride Mesocellular carbon foam Electrochemistry

An atmosphere-breathing propulsion system using inductively coupled plasma source

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Chinese Journal of Aeronautics 2023年第5期36卷 223-238页

作者： Peng ZHENG Jianjun wu Yu zhang Bixuan CHE Yuanzheng zhao College of Aerospace Science and Engineering National University of Defense TechnologyChangsha 410073China

CubeSats have attracted more research interest recently due to their lower cost and shorter production time.A promising technology for CubeSat application is atmosphere-breathing electric propulsion,which can capture the atmospheric particles as propulsion propellant to maintain longterm mission at very low Earth orbit.This paper designs an atmosphere-breathing electric propulsion system for a 3 U CubeSat,which consists of an intake device and an electric thruster based on the inductively coupled plasma.The capture performance of intake device is optimized considering both particles capture efficiency and compression ratio.The plasma source is also analyzed by experiment and simulation.Then,the thrust performance is also estimated when taking into account the intake performance.The results show that it is feasible to use atmosphere-breathing electric propulsion technology for CubeSats to compensate for aerodynamic drag at lower Earth orbit.

关键词： Atmosphere-Breathing Electric Propulsion(ABEP) CubeSat Inductively coupled plasma Intake device Very Low Earth Orbit(VLEO)

Intelligent prediction of slope stability based on visual exploratory data analysis of 77 in situ cases

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International Journal of Mining Science and Technology 2023年第1期33卷 47-59页

作者： Guangjin Wang Bing zhao Bisheng wu Chao zhang Wenlian Liu Faculty of Land Resources Engineering Kunming University of Science and TechnologyKunming 650093China Yunnan International Technology Transfer Center for Mineral Resources Development and Solid Waste Resource Utilization Kunming 650093China State Key Laboratory of Hydroscience and Engineering Department of Hydraulic EngineeringTsinghua UniversityBeijing 100084China State Key Laboratory of Geomechanics and Geotechnical Engineering Institute of Rock and Soil MechanicsChinese Academy of SciencesWuhan 430071China China Nonferrous Metals Industry Kunming Survey and Design Research Institute Co.Ltd Kunming 650051China

Slope stability prediction research is a complex non-linear system problem.In carrying out slope stability prediction work,it often encounters low accuracy of prediction models and blind data preprocessing.Based on 77 field cases,5 quantitative indicators are selected to improve the accuracy of prediction models for slope stability.These indicators include slope angle,slope height,internal friction angle,cohesion and unit weight of rock and soil.Potential data aggregation in the prediction of slope stability is analyzed and visualized based on Six-dimension reduction methods,namely principal components analysis(PCA),Kernel PCA,factor analysis(FA),independent component analysis(ICA),non-negative matrix factorization(NMF)and t-SNE(stochastic neighbor embedding).Combined with classic machine learning methods,7 prediction models for slope stability are established and their reliabilities are examined by random cross validation.Besides,the significance of each indicator in the prediction of slope stability is discussed using the coefficient of variation method.The research results show that dimension reduction is unnecessary for the data processing of prediction models established in this paper of slope stability.Random forest(RF),support vector machine(SVM)and k-nearest neighbour(KNN)achieve the best prediction accuracy,which is higher than 90%.The decision tree(DT)has better accuracy which is 86%.The most important factor influencing slope stability is slope height,while unit weight of rock and soil is the least significant.RF and SVM models have the best accuracy and superiority in slope stability prediction.The results provide a new approach toward slope stability prediction in geotechnical engineering.

关键词： Slope stability prediction Machine learning algorithm Dimensionality reduction visualization Random cross validation Coefficient of variation