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Using the Phosphomannose Isomerase (PMI) Gene from Saccharomyces cerevisiae for Selection in Rice Transformation

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Journal of Integrative Agriculture 2012年第9期11卷 1391-1398页

作者： WANG Tao LIU Liang-yu TANG Yong-yan zhang Xiao-bo zhang Mei-dong ZHENG Yong-lian zhang fang-dong National Key Laboratory of Crop Genetic Improvement Ministry of Science and Technology/Huazhong Agricultural University Wuhan 430070P. R. China

The phosphomannose isomerase （PMI） gene from Saccharomyces cerevisiae acted as selectable marker and mannose acted as selective agent for the production of transgenic plants of rice （Oryza sativa L.） via Agrobacterium-mediated transformation. The concentration of mannose during the selection was stepwise increased, 5 g L-1 mannose combined with 15 g L-1 sucrose and 500 mg L-1 cefotaxime was used in the initial selection stage, then the concentration of mannose was increased to 11 g L-1, the highest transformation rate was 20.0%. The integration of PMI gene was confirmed by PCR, and the result of RT-PCR assay proved that the intron of PMI gene can be excised correctly during RNA splicing. 13- Glucuronidase （GUS） activity analysis confirmed the expression of GUS gene. All those means the PMI gene from yeast can be used as a selectable marker in rice transformation.

关键词： phosphomannose isomerase selectable marker Saccharomyces cerevisiae transformation rice

Prediction of dissolved gas content in transformer oil based on multi-information fusion

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High Voltage 2024年第3期9卷 685-699页

作者： Tongliang Yang Yun fang Chengming zhang Chao Tang dong Hu College of Engineering and Technology Southwest UniversityChongqingChina International R&D Center for New Technologies of Smart Grid and Equipment Southwest UniversityChongqingChina

In order to accurately predict the content and variation trend of dissolved gas in trans-former oil and guide the condition maintenance of power transformers,a combined prediction model based on multi-information fusion is proposed and its effectiveness is *** of all,based on the possibility of pathological and missing historical sample data,a detection and filling method based on variable weight combination samples is ***,the authors propose two *** at the non-linear and non-stationary characteristics of gas content,a univariate decomposition prediction mode HBA-VMD-TCN which based on the Honey Badger algorithm,variational mode decomposition and time convolutional network(TCN)is *** the multi-variate Informer prediction model is established for gas content affected by multiple ***,the cross-entropy theory is used to determine the weight coefficients of the two models,and the multi-information fusion combined prediction model is ***,on the basis of the above,a method to determine the time step and the position information of the transition point adaptively in the process of prediction is proposed to further improve the prediction *** results show that,through a series of simulation experiments of model comparison and transformer anomaly prediction,the accuracy and effectiveness of the combined prediction model are verified.

关键词： content prediction dissolved

Imitation Learning Based Real-time Decision-making of Microgrid Economic Dispatch Under Multiple Uncertainties

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Journal of Modern Power Systems and Clean Energy 2024年第4期12卷 1183-1193页

作者： Wei dong Fan zhang Meng Li Xiaolun fang Qiang Yang School of Automation Hangzhou Dianzi UniversityHangzhou 310018China College of Electrical Engineering Zhejiang UniversityHangzhou 310027China

The intermittency of renewable energy generation,variability of load demand,and stochasticity of market price bring about direct challenges to optimal energy management of *** cope with these different forms of operation un-certainties,an imitation learning based real-time decision-mak-ing solution for microgrid economic dispatch is *** this solution,the optimal dispatch trajectories obtained by solv-ing the optimal problem using historical deterministic operation patterns are demonstrated as the expert samples for imitation *** improve the generalization performance of imita-tion learning and the expressive ability of uncertain variables,a hybrid model combining the unsupervised and supervised learn-ing is *** denoising autoencoder based unsupervised learning model is adopted to enhance the feature extraction of operation ***,the long short-term memory network based supervised learning model is used to efficiently characterize the mapping between the input space composed of the extracted operation patterns and system state variables and the output space composed of the optimal dispatch *** numerical simulation results demonstrate that under vari-ous operation uncertainties,the operation cost achieved by the proposed solution is close to the minimum theoretical *** with the traditional model predictive control method and basic clone imitation learning method,the operation cost of the proposed solution is reduced by 6.3%and 2.8%,respective-ly,overa test period of three months.

关键词： Energy management imitation learning datadriven decision economic dispatch

A New Method for Solving Nonlinear Partial Differential Equations Based on Liquid Time-Constant Networks

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Journal of Systems Science & Complexity 2024年第2期37卷 480-493页

作者： SUN Jiuyun dong Huanhe fang Yong College of Mathematics and Systems Science Shandong University of Science and TechnologyQingdao 266590China

In this paper,physics-informed liquid networks(PILNs)are proposed based on liquid time-constant networks(LTC)for solving nonlinear partial differential equations(PDEs).In this approach,the network state is controlled via ordinary differential equations(ODEs).The significant advantage is that neurons controlled by ODEs are more expressive compared to simple activation *** addition,the PILNs use difference schemes instead of automatic differentiation to construct the residuals of PDEs,which avoid information loss in the neighborhood of sampling *** this method draws on both the traveling wave method and physics-informed neural networks(PINNs),it has a better physical ***,the KdV equation and the nonlinear Schr¨odinger equation are solved to test the generalization ability of the *** the best of the authors’knowledge,this is the first deep learning method that uses ODEs to simulate the numerical solutions of PDEs.

关键词： Nonlinear partial differential equations numerical solutions physics-informed liquid networks physics-informed neural networks

A hybrid RNA-protein biosensor for high-throughput screening of adenosylcobalamin biosynthesis

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Synthetic and Systems Biotechnology 2024年第3期9卷 513-521页

作者： Xia Yang Huiying Wang dongqin Ding Huan fang Huina dong Dawei zhang College of Biological and Pharmaceutical Sciences China Three Gorges UniversityYichangHubei443002China Tianjin Institute of Industrial Biotechnology Chinese Academy of SciencesTianjin300308China Key Laboratory of Engineering Biology for Low-Carbon Manufacturing Tianjin Institute of Industrial BiotechnologyChinese Academy of SciencesTianjin300308China University of Chinese Academy of Sciences Beijing100049China

Genetically encoded circuits have been successfully utilized to assess and characterize target variants with desirable traits from large mutant *** is an essential coenzyme that is required in many intracellular physiological reactions and is widely used in the pharmaceutical and food ***-throughput screening techniques capable of detecting adenosylcobalamin productivity and selecting superior adenosylcobalamin biosynthesis strains are critical for the creation of an effective microbial cell factory for the production of adenosylcobalamin at an industrial *** this study,we developed an RNA-protein hybrid biosensor whose input part was an endogenous RNA riboswitch to specifically respond to adenosylcobalamin,the inverter part was an orthogonal transcriptional repressor to obtain signal inversion,and the output part was a fluorescent protein to be easily *** hybrid biosensor could specifically and positively correlate adenosylcobalamin concentrations to green fluorescent protein expression levels in *** study also improved the operating concentration and dynamic range of the hybrid biosensor by systematic *** individual cell harboring the hybrid biosensor presented over 20-fold higher fluorescence intensity than the negative ***,using such a biosensor combined with fluorescence-activated cell sorting,we established a high-throughput screening platform for screening adenosylcobalamin *** study demonstrates that this platform has significant potential to quickly isolate high-productive strains to meet industrial demand and that the framework is acceptable for various metabolites.

关键词： Adenosylcobalamin Genetically encoded biosensor Riboswitch Transcriptional repressor High-throughput screening

Stomatal dynamics are regulated by leaf hydraulic traits and guard cell anatomy in nine true mangrove species

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Plant Diversity 2024年第3期46卷 395-405页

作者： Ya-dong Qie Qi-Wei zhang Scott A.M.McAdam Kun-fang Cao State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources College of ForestryGuangxi UniversityNanning 530004China Guangxi Key Laboratory of Forest Ecology and Conservation College of ForestryGuangxi UniversityNanning 530004China Key Laboratory of Ecology of Rare and Endangered Species and Environmental Protection Ministry of EducationGuangxi Normal UniversityGuilin 541001China Guangxi Key Laboratory of Landscape Resources Conservation and Sustainable Utilization in Lijiang River Basin Guangxi Normal UniversityGuilin 541001China Purdue Center for Plant Biology Department of Botany and Plant PathologyPurdue UniversityWest LafayetteIN 47907USA

Stomatal regulation is critical for mangroves to survive in the hyper-saline intertidal zone where water stress is severe and water availability is highly ***,very little is known about the stomatal sensitivity to vapour pressure deficit(VPD)in mangroves,and its co-ordination with stomatal morphology and leaf hydraulic *** measured the stomatal response to a step increase in VPD in situ,stomatal anatomy,leaf hydraulic vulnerability and pressure-volume traits in nine true mangrove species of five families and collected the data of genome *** aimed to answer two questions:(1)Does stomatal morphology influence stomatal dynamics in response to a high VPD in mangroves?with a consideration of possible influence of genome size on stomatal morphology;and(2)do leaf hydraulic traits influence stomatal sensitivity to VPD in mangroves?We found that the stomata of mangrove plants were highly sensitive to a step rise in VPD and the stomatal responses were directly affected by stomatal anatomy and hydraulic ***,denser stomata was correlated with faster stomatal closure at high VPD across the species of Rhizophoraceae,and stomata size negatively and vein density positively correlated with genome *** negative leaf osmotic pressure at the full turgor(πo)was related to higher operating steady-state stomatal conductance(gs);and a higher leaf capacitance(Cleaf)and more embolism resistant leaf xylem were associated with slower stomatal responses to an increase in *** addition,stomatal responsiveness to VPD was indirectly affected by leaf morphological traits,which were affected by site salinity and consequently leaf water *** results demonstrate that mangroves display a unique relationship between genome size,stomatal size and vein packing,and that stomatal responsiveness to VPD is regulated by leaf hydraulic traits and stomatal *** work provides a quantitative framework to better understand of stomatal regulation in mangroves

关键词： Stomatal temporal kinetics Vapour-pressure deficit(VPD) Leaf water relations Leaf hydraulic vulnerability Leaf osmotic potential Genome size

Experimental study on wax deposition of highly paraffinic oil in intermittent gas-oil flow in pipelines

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Petroleum Science 2024年第3期21卷 2080-2088页

作者： Chuan-Shuo Wang Qian-Li Ma Xiao-fang Lv Jie zhang Yang Liu Shi-dong Zhou Jiangsu Key Laboratory of Oil and Gas Storage and Transportation Technology Changzhou UniversityChangzhou213164JiangsuPR China Hade Oil and Gas Development Department Tarim Oilfield BranchKorla841000XinjiangPR China

Oil-gas two phase wax deposition is a fairly common and open-ended question in flow assurance of multiphase transportation *** paper investigated the two main aspects of oil-gas two phase wax deposition layer:apparent thickness and crystal structure characteristics.A typical highly paraffinic oil in Bohai Sea,China,was used as the experimental material to investigate the wax deposition thickness in oil-gas two phase under the influence of different oil temperatures,superficial gas/liquid phase velocities and gas-oil ratios by using multiphase flow loop experimental *** as in the classical theory of wax molecular diffusion,it showed that wax deposition thickness of oil-gas two phase increased with increasing oil *** of the impact of different superficial phase velocities found that the actual liquid flow heat transfer and shear stripping was the gas phase dominant mechanisms determining wax deposit *** addition,the crystal structure of the wax deposition layer was characterized with the help of small-angle X-ray scattering(SAXS)for different circumferential positions,flow rates and gas-oil *** bottom deposition layer had a complex crystal structure and high hardness,which were subject to change over flow rate ***,the SAXS results provided evidence that the indirect effect of the actual liquid velocity modified by the gas phase was the main *** study of the effect of gas phase on the wax deposition of oil-gas two phase will help shed light onto the mechanism by which this important process *** findings address a very urgent need in the field of wax deposition of highly paraffinic oil to understand the flow security of oilgas two phase that occurs easily in multiphase field pipelines.

关键词： Oil-gas two phase Highly paraffinic oil Wax deposition SAXS

Thermal stability improvement and microstructure optimization of high cobalt content Nd-Fe-B magnets via terbium grain boundary diffusion

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Journal of Rare Earths 2024年第8期42卷 1531-1538,I0004页

作者： Jiyuan Xu Ruiyang Meng Jing Liu Jiateng zhang Rui Han Yikun fang Shengzhi dong Wei Li Division of Functional Materials Research Central Iron and Steel Research InstituteBeijing100081China

The substitution of Fe by Co in the 2:14:1 phase is an effective method to increase the Curie temperature and enhance the thermal stability of the Nd-Fe-B ***,the accumulation of Co ele ment at the grain boundaries(GBs) changes the GBs from nonmagnetic to ferromagnetic and causes the thinlayer GBs to become rare,In this paper,the method of diffusing Tb element was chosen to improve the microstructure and temperature stability of high-Co *** original sintered Nd_(28.5)Dy_(3)-CO_(x)e_(bal)M_(0.6)B_(i)(x=0,6 wt%,12 wt%;M = Cu,Al,Zr) magnets with different Co contents were diffused with Tb by grain boundary diffusion(GBD).After GBD,high-Co magnets exhibit more continuously distributed thin-layer GBs,and their thermal stability is significantly *** high-Co magnets(x=6 wt%),the absolute value of the temperature coefficient of coercivity decreases from 0.603%/K to0.508%/K in the temperature range of 293-413 K,that of remanence decreases from 0.099%/K to 0.091%/K,and the coercivity increases from 18.44 to 25.04 *** electron microscopy(TEM)characterization reveals that there are both the 1:2 phase and the amorphous phase in the high-Co magnet before and after GBD,EDS elemental analysis shows that Tb element is more likely to preferentially replace the rare earth elements in the 2:14:1 main phase than in the 1:2 phase and the amorphous *** concentration of Tb at the edge of the main phase is much higher than that in the 1:2phase and amorphous phase,which is beneficial to the improvement of the *** preferential replacement of Tb elements at the edge of the 2:14:1 phase and thin-layer GBs with a more continuous distribution are synergistically responsible for improving the thermal stability of high-Co *** study indicates that GBD is an effective method to improve the microstructure and thermal stability of high-Co magnets.

关键词： Nd-Fe-B magnets Coercivity Grain boundary diffusion Thermal stability Micro structure Rare earths

Physical informed memory networks for solving PDEs:implementation and applications

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Communications in Theoretical Physics 2024年第2期76卷 51-61页

作者： Jiuyun Sun Huanhe dong Yong fang College of Mathematics and Systems Science Shandong University of Science and TechnologyQingdao 266590China

With the advent of physics informed neural networks(PINNs),deep learning has gained interest for solving nonlinear partial differential equations(PDEs)in recent *** this paper,physics informed memory networks(PIMNs)are proposed as a new approach to solving PDEs by using physical laws and dynamic behavior of *** the fully connected structure of the PINNs,the PIMNs construct the long-term dependence of the dynamics behavior with the help of the long short-term memory ***,the PDEs residuals are approximated using difference schemes in the form of convolution filter,which avoids information loss at the neighborhood of the sampling ***,the performance of the PIMNs is assessed by solving the Kd V equation and the nonlinear Schr?dinger equation,and the effects of difference schemes,boundary conditions,network structure and mesh size on the solutions are *** show that the PIMNs are insensitive to boundary conditions and have excellent solution accuracy even with only the initial conditions.

关键词： nonlinear partial differential equations physics informed memory networks physics informed neural networks numerical solution