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Strigolactones modulate cotton fiber elongation and secondary cell wall thickening

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Journal of Integrative Agriculture 2024年第6期23卷 1850-1863页

作者： Yunze Wen Peng He Xiaohan Bai Huizhi zhang yunfeng zhang Jianing Yu College of Life Sciences Shaanxi Normal UniversityXi’an 710119China

Cotton is one of the most important economic crops in the world,and it is a major source of fiber in the textile industry.Strigolactones(SLs)are a class of carotenoid-derived plant hormones involved in many processes of plant growth and development,although the functions of SL in fiber development remain largely unknown.Here,we found that the endogenous SLs were significantly higher in fibers at 20 days post-anthesis(DPA).Exogenous SLs significantly increased fiber length and cell wall thickness.Furthermore,we cloned three key SL biosynthetic genes,namely GhD27,GhMAX3,and GhMAX4,which were highly expressed in fibers,and subcellular localization analyses revealed that GhD27,GhMAX3,and GhMAX4 were localized in the chloroplast.The exogenous expression of GhD27,GhMAX3,and GhMAX4 complemented the physiological phenotypes of d27,max3,and max4 mutations in Arabidopsis,respectively.Knockdown of GhD27,GhMAX3,and GhMAX4 in cotton resulted in increased numbers of axillary buds and leaves,reduced fiber length,and significantly reduced fiber thickness.These findings revealed that SLs participate in plant growth,fiber elongation,and secondary cell wall formation in cotton.These results provide new and effective genetic resources for improving cotton fiber yield and plant architecture.

关键词： strigolactones fiber elongation secondary cell wall thickening cotton

Recent progress in CdS-based S-scheme photocatalysts

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Journal of Materials Science & Technology 2024年第4期171卷 162-184页

作者： Yajing Ren yunfeng Li Guixu Pan Ning Wang Yan Xing Zhenyi zhang College of Environmental and Chemical Engineering Xi’an Polytechnic UniversityXi’an 710048China Jilin Provincial Key Laboratory of Advanced Energy Materials Department of ChemistryNortheast Normal UniversityChangchun 130024China Key Laboratory of New Energy and Rare Earth Resource Utilization of State Ethnic Affairs Commission Key Laboratory of Photosensitive Materials and Devices of Liaoning ProvinceSchool of Physics and Materials EngineeringDalian Minzu UniversityDalian 116600China

Photocatalytic technology with sunlight as driving force can convert solar energy into other energy sources for storage and further use.Cadmium sulfide(CdS),as a typical reducing semiconductor of metal sulfides,represents an interesting research hotspot in photocatalysis due to its suitable bandgap(2.4 eV)for utilizing visible light and strong reducing ability for inducing surface catalytic reactions.Unfortunately,the photocatalytic performance of CdS is still limited by its fast carrier recombination and serious pho-tocorrosion.So far,CdS semiconductor has been widely developed as a typical reducing photocatalyst in constructing novel S-scheme heterojunction to overcome the above drawbacks.In this review,the de-sign concepts,basic principles,and charge transfer characteristics of CdS-based S-scheme heterojunction photocatalysts have been comprehensively introduced.Several advanced and effective characterization methods for studying the mechanism of CdS-based S-scheme heterojunction are analyzed in detail.Fur-thermore,we also summarize the typical applications of CdS-based S-scheme heterojunctions for water splitting,CO_(2) reduction,pollutant degradation,etc.Eventually,according to the current investigation sta-tus,some drawbacks in the current synthetic strategy,mechanism exploration,and application prospect of CdS-based S-scheme heterojunction are proposed,which need to be addressed by further expansion and innovative research.

关键词： Photocatalysis CdS semiconductor Heterojunction S-scheme Metal sulfide

Tube Model Predictive Control Based Cyber-attack-resilient Optimal Voltage Control Strategy in Wind Farms

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CSEE Journal of Power and Energy Systems 2024年第2期10卷 530-538页

作者： Zhenming Li Minghao Wang yunfeng Yan Donglian Qi Zhao Xu Jianliang zhang Zezhou Wang College of Electrical Electronic Engineering Zhejiang UniversityHangzhou 310058China Department of Electrical Engineering The Hong Kong Polytechnic UniversityKowloonHong KongChina Haiyan power supply company of State Grid Zhejiang Electric Power Co. LtdHangzhouChina

Optimal voltage controls have been widely applied in wind farms to maintain voltage stability of power grids.In order to achieve optimal voltage operation,authentic grid information is widely needed in the sensing and actuating processes.However,this may induce system vulnerable to malicious cyber-attacks.To this end,a tube model predictive control-based cyber-attack-resilient optimal voltage control method is proposed to achieve voltage stability against malicious cyber-attacks.The proposed method consists of two cascaded model predictive controllers(MPC),which outperform other peer control methods in effective alleviation of adverse effects from cyber-attacks on actuators and sensors of the system.Finally,efficiency of the proposed method is evaluated in sensor and actuator cyber-attack cases based on a modified IEEE 14 buses system and IEEE 118 buses system.Index Terms-Attack-resilient control,optimal voltage control,tube-based model predictive control,wind farm-connected power system.

关键词： Attack-resilient control optimal voltage control tube-based model predictive control wind farm-connected power system

Noise-Tolerant ZNN-Based Data-Driven Iterative Learning Control for Discrete Nonaffine Nonlinear MIMO Repetitive Systems

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IEEE/CAA Journal of Automatica Sinica 2024年第2期11卷 344-361页

作者： yunfeng Hu Chong zhang Bo Wang Jing Zhao Xun Gong Jinwu Gao Hong Chen State Key Laboratory of Automotive Simulation and Control Jilin UniversityJilin UniversityChangchun 130025China College of Communication Engineering Jilin UniversityJilin UniversityChangchun 130025China Department of Electromechanical Engineering University of MacaoMacao 999078China School of Artificial Intelligence Jilin UniversityChangchun 130012China IEEE College of Electronics and Information Engineering Tongji UniversityShanghai 200092China

Aiming at the tracking problem of a class of discrete nonaffine nonlinear multi-input multi-output(MIMO) repetitive systems subjected to separable and nonseparable disturbances, a novel data-driven iterative learning control(ILC) scheme based on the zeroing neural networks(ZNNs) is proposed. First, the equivalent dynamic linearization data model is obtained by means of dynamic linearization technology, which exists theoretically in the iteration domain. Then, the iterative extended state observer(IESO) is developed to estimate the disturbance and the coupling between systems, and the decoupled dynamic linearization model is obtained for the purpose of controller synthesis. To solve the zero-seeking tracking problem with inherent tolerance of noise,an ILC based on noise-tolerant modified ZNN is proposed. The strict assumptions imposed on the initialization conditions of each iteration in the existing ILC methods can be absolutely removed with our method. In addition, theoretical analysis indicates that the modified ZNN can converge to the exact solution of the zero-seeking tracking problem. Finally, a generalized example and an application-oriented example are presented to verify the effectiveness and superiority of the proposed process.

关键词： Adaptive control control system synthesis data-driven iterative learning control neurocontroller nonlinear discrete time systems

Damage evolution and removal behaviors of GaN crystals involved in double-grits grinding

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International Journal of Extreme Manufacturing 2024年第2期6卷 469-484页

作者： Chen Li Yuxiu Hu Zongze Wei Chongjun Wu yunfeng Peng Feihu zhang Yanquan Geng State Key Laboratory of Robotics and System(HIT) Harbin Institute of TechnologyHarbin 150001People’s Republic of China Key Laboratory of Microsystems and Microstructures Manufacturing(HIT) Harbin Institute of TechnologyHarbin 150001People’s Republic of China College of Mechanical Engineering Donghua UniversityShanghai 201620People’s Republic of China Department of Mechanical and Electrical Engineering Xiamen UniversityXiamen 361005People’s Republic of China

Elucidating the complex interactions between the work material and abrasives during grinding of gallium nitride(GaN)single crystals is an active and challenging research area.In this study,molecular dynamics simulations were performed on double-grits interacted grinding of GaN crystals;and the grinding force,coefficient of friction,stress distribution,plastic damage behaviors,and abrasive damage were systematically investigated.The results demonstrated that the interacted distance in both radial and transverse directions achieved better grinding quality than that in only one direction.The grinding force,grinding induced stress,subsurface damage depth,and abrasive wear increase as the transverse interacted distance increases.However,there was no clear correlation between the interaction distance and the number of atoms in the phase transition and dislocation length.Appropriate interacted distances between abrasives can decrease grinding force,coefficient of friction,grinding induced stress,subsurface damage depth,and abrasive wear during the grinding process.The results of grinding tests combined with cross-sectional transmission electron micrographs validated the simulated damage results,i.***.amorphous atoms,high-pressure phase transition,dislocations,stacking faults,and lattice distortions.The results of this study will deepen our understanding of damage accumulation and material removal resulting from coupling between abrasives during grinding and can be used to develop a feasible approach to the wheel design of ordered abrasives.

关键词： grinding double-grits molecular dynamics damage material removal gallium nitride

Modeling and prediction of tribological properties of copper/aluminum-graphite self-lubricating composites using machine learning algorithms

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Friction 2024年第6期12卷 1322-1340页

作者： Huifeng NING Faqiang CHEN yunfeng SU Hongbin LI Hengzhong FAN Junjie SONG Yongsheng zhang Litian HU School of Electrical and Mechanical Engineering Lanzhou University of TechnologyLanzhou 730050China State Key Laboratory of Solid Lubrication Lanzhou Institute of Chemical PhysicsChinese Academy of SciencesLanzhou 730000China Center of Materials Science and Optoelectronics Engineering University of Chinese Academy of SciencesBeijing 100049China

The tribological properties of self-lubricating composites are influenced by many variables and complex mechanisms.Data-driven methods,including machine learning(ML)algorithms,can yield a better comprehensive understanding of complex problems under the influence of multiple parameters,typically for how tribological performances and material properties correlate.Correlation of friction coefficients and wear rates of copper/aluminum-graphite(Cu/Al-graphite)self-lubricating composites with their inherent material properties(composition,lubricant content,particle size,processing process,and interfacial bonding strength)and the variables related to the testing method(normal load,sliding speed,and sliding distance)were analyzed using traditional approaches,followed by modeling and prediction of tribological properties through five different ML algorithms,namely support vector machine(SVM),K-Nearest neighbor(KNN),random forest(RF),eXtreme gradient boosting(XGBoost),and least-squares boosting(LSBoost),based on the tribology experimental data.Results demonstrated that ML models could satisfactorily predict friction coefficient and wear rate from the material properties and testing method variables data.Herein,the LSBoost model based on the integrated learning algorithm presented the best prediction performance for friction coefficients and wear rates,with R2 of 0.9219 and 0.9243,respectively.Feature importance analysis also revealed that the content of graphite and the hardness of the matrix have the greatest influence on the friction coefficients,and the normal load,the content of graphite,and the hardness of the matrix influence the wear rates the most.

关键词： self-lubricating composites machine learning(ML) tribological properties prediction

Transdermal treatment for malignant melanoma by aptamer-modified tetrahedral framework nucleic acid delivery of vemurafenib

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Chinese Chemical Letters 2024年第4期35卷 260-267页

作者： Dexuan Xiao Tianyu Chen Tianxu zhang Sirong Shi Mei zhang Xin Qin Yunkun Liu Longjiang Li yunfeng Lin State Key Laboratory of Oral Diseases National Clinical Research Center for Oral DiseasesWest China Hospital of StomatologySichuan UniversityChengdu 610041China Sichuan Provincial Engineering Research Center of Oral Biomaterials Chengdu 610041China Department of Head and Neck Oncology National Clinical Research Center for Oral DiseasesWest China Hospital of StomatologySichuan UniversityChengdu 610041China

Melanoma is one of the most malignant skin tumors, whose high invasion is generally associated with BRAF gene mutation. Although new chemotherapeutic drugs, such as vemurafenib, have been developed to inhibit the growth of melanoma, these drugs are usually administered intravenously or orally, resulting in toxic side effects on major tissues and organs. Tetrahedral framework nucleic acids(tFNAs) are a novel type of DNA nanostructures with excellent biocompatibility and versatility which have been proven to penetrate through skin barrier with ease. In this study, we prepared t FNAs with vemurafenib and connected DNA aptamer AS1411 at the apex of t FNAs(AS1411-tFNAs/vemurafenib). On one hand, AS1411-tFNAs/vemurafenib could kill melanoma cells by blocking the mutated BRAF gene in vitro. Compared with free vemurafenib, AS1411-tFNAs/vemurafenib had no obvious toxicity to normal cells. On the other hand,AS1411-tFNAs could transfer vemurafenib to cross through the skin barrier and permeate into tumor tissues. In vivo, transdermal delivery of AS1411-t FNAs/vemurafenib could inhibit the growth of human A375melanoma, whose inhibiting effect was stronger than intravenous administration of vemurafenib. These results demonstrated the application prospects of tFNAs combined with chemotherapeutic drugs in skin tumors.

关键词： Melanoma Vemurafenib DNA nanostructure Transdermal treatment Side effect

DNA framework signal amplification platform-based highthroughput systemic immune monitoring

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Signal Transduction and Targeted Therapy 2024年第3期9卷 1115-1131页

作者： Ye Chen Xingyu Chen Bowen zhang Yuxin zhang Songhang Li Zhiqiang Liu Yang Gao Yuxuan Zhao Lin Yan Yi Li Taoran Tian yunfeng Lin State Key Laboratory of Oral Diseases National Center for StomatologyNational Clinical Research Center for Oral DiseasesWest China Hospital of StomatologySichuan UniversityChengdu 610041 SichuanPR China Department of Prosthodontics Tianjin Stomatological HospitalSchool of MedicineNankai UniversityTianjin 300041PR China Department of Laboratory Medicine West China HospitalSichuan UniversityChengdu 610041 SichuanPR China Sichuan Provincial Engineering Research Center of Oral Biomaterials Chengdu 610041 SichuanChina

Systemic immune monitoring is a crucial clinical tool for disease early diagnosis,prognosis and treatment planning by quantitative analysis of immune cells.However,conventional immune monitoring using flow cytometry faces huge challenges in large-scale sample testing,especially in mass health screenings,because of time-consuming,technical-sensitive and high-cost features.However,the lack of high-performance detection platforms hinders the development of high-throughput immune monitoring technology.To address this bottleneck,we constructed a generally applicable DNA framework signal amplification platform(DSAP)based on post-systematic evolution of ligands by exponential enrichment and DNA tetrahedral framework-structured probe design to achieve high-sensitive detection for diverse immune cells,including CD4+,CD8+T-lymphocytes,and monocytes(down to 1/100μl).Based on this advanced detection platform,we present a novel high-throughput immune-cell phenotyping system,DSAP,achieving 30-min one-step immune-cell phenotyping without cell washing and subset analysis and showing comparable accuracy with flow cytometry while significantly reducing detection time and cost.As a proof-of-concept,DSAP demonstrates excellent diagnostic accuracy in immunodeficiency staging for 107 HIV patients(AUC>0.97)within 30 min,which can be applied in HIV infection monitoring and screening.Therefore,we initially introduced promising DSAP to achieve high-throughput immune monitoring and open robust routes for point-of-care device development.

关键词： diagnosis monitoring initially

Improvement effect of reversible solid solutions Mg_(2)Ni(Cu)/Mg_(2)Ni(Cu)H_(4)on hydrogen storage performance of MgH_(2)

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Journal of Magnesium and Alloys 2024年第1期12卷 197-208页

作者： Yingyan Zhao Zhibing Liu Jiangchuan Liu yunfeng Zhu Jiguang zhang Yana Liu Xiaohui Hu Liquan Li College of Materials Science and Engineering Nanjing Tech University30 South Puzhu RoadNanjing211816PR China Jiangsu Collaborative Innovation Centre for Advanced Inorganic Function Composites Nanjing Tech UniversityNanjing211816PR China

The hydrogen absorption/desorption kinetic properties of MgH_(2)can be effectively enhanced by doping specific catalysts.In this work,MOFs-derived NiCu@C nanoparticles(~15 nm)with regular core-shell structure were successfully prepared and introduced into MgH_(2)(denoted as MgH_(2)-NiCu@C).The onset and peak temperatures of hydrogen desorption of MgH_(2)-11 wt.%NiCu@C are 175.0℃and282.2℃,respectively.The apparent activation energy of dehydrogenated reaction is 77.2±4.5 kJ/mol for MgH_(2)-11 wt.%NiCu@C,which is lower than half of that of the as-milled MgH_(2).Moreover,MgH_(2)-11 wt.%NiCu@C displays great cyclic stability.The strengthening"hydrogen pumping"effect of reversible solid solutions Mg_(2)Ni(Cu)/Mg_(2)Ni(Cu)H_(4)is proposed to explain the remarkable improvement in hydrogen absorption/desorption kinetic properties of MgH_(2).This work offers a novel perspective for the design of bimetallic nanoparticles and beyond for application in hydrogen storage and other energy related fields.

关键词： Magnesium hydride Reversible solid solution Core-shell nanoparticles Hydrogen storage performance