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| 1 | Genome-wide association study of vitamin E in sweet corn kernels显示文摘Vitamin E,consisting of tocopherols and tocotrienols,serves as a lipid-soluble antioxidant in sweet corn kernels,providing nutrients to both plants and humans.Though the key genes involved in the vitamin E biosynthesis pathway have been identified in plants,the genetic architecture of vitamin E content in sweet corn kernels remains largely unclear.In the present study,an association panel of 204 inbred lines of sweet corn was constructed.Seven compounds of vitamin E were quantified in sweet corn kernels at 28 days after pollination.A total of 119 loci for vitamin E were identified using a genome-wide association study based on genotyping by sequencing,and a genetic network of vitamin E was constructed.Candidate genes identified were involved mainly in RNA regulation and protein metabolism.The known gene ZmVTE4,encodingγ-tocopherol methyltransferase,was significantly associated with four traits(α-tocopherol,α-tocotrienol,theα/γ-tocopherol ratio,and theα/γ-tocotrienol ratio).The effects of two causative markers on ZmVTE4 were validated by haplotype analysis.Finally,two elite cultivars(Yuetian 9 and Yuetian 22)with a 4.5-fold increase in the sum ofα-andγ-tocopherols were developed by marker-assisted selection,demonstrating the successful biofortification of sweet corn.Three genes(DAHPS,ADT2,and cmu2)involved in chorismate and tyrosine synthesis were significantly associated with theα/γ-tocotrienol ratio.These results shed light on the genetic architecture of vitamin E and may accelerate the nutritional improvement of sweet corn. | Yingni Xiao Yongtao Yu Gaoke Li Lihua Xie Xinbo Guo Jiansheng Li Yuliang Li Jianguang Hu | 2020 | The Crop Journal2020，8，2： | 7 |
| 2 | Eigen microstates and their evolutions in complex systems显示文摘Emergence refers to the existence or formation of collective behaviors in complex systems.Here,we develop a theoretical framework based on the eigen microstate theory to analyze the emerging phenomena and dynamic evolution of complex system.In this framework,the statistical ensemble composed of M microstates of a complex system with N agents is defined by the normalized N×M matrix A,whose columns represent microstates and order of row is consist with the time.The ensemble matrix A can be decomposed as■,where r=min(N,M),eigenvalueσIbehaves as the probability amplitude of the eigen microstate U_I so that■and U_I evolves following V_I.In a disorder complex system,there is no dominant eigenvalue and eigen microstate.When a probability amplitudeσIbecomes finite in the thermodynamic limit,there is a condensation of the eigen microstate UIin analogy to the Bose–Einstein condensation of Bose gases.This indicates the emergence of U_I and a phase transition in complex system.Our framework has been applied successfully to equilibrium threedimensional Ising model,climate system and stock markets.We anticipate that our eigen microstate method can be used to study non-equilibrium complex systems with unknown orderparameters,such as phase transitions of collective motion and tipping points in climate systems and ecosystems. | Yu Sun Gaoke Hu Yongwen Zhang Bo Lu Zhenghui Lu Jingfang Fan Xiaoteng Li Qimin Deng Xiaosong Chen | 2021 | Communications in Theoretical Physics2021，73，6： | 5 |
| 3 | Comparative transcriptome analysis of sweet corn seedlings under low-temperature stress显示文摘Stress induced by low temperature, which represents a widespread environmental factor,strongly affects maize growth and yield. However, the physiological characteristics and molecular regulatory mechanisms of maize seedlings in response to cold remain poorly understood. In this study, using RNA-seq, we investigated the transcriptome profiles of two sweet com inbred lines, 'Richao'(RC) and C5, under cold stress. A total of 357 and 455 differentially expressed genes(DEGs) were identified in the RC and C5 lines, respectively, 94 DEGs were detected as common DEGs related to cold response in both genotypes, and a total of 589 DEGs were detected as cold tolerance-associated genes. By combining protein function clustering analysis and significantly enriched Gene Ontology(GO) terms analysis,we suggest that transcription factors may play a dominating role in the cold stress response and tolerance of sweet com. Furthermore, 74 differentially expressed transcription factors were identified, of those many genes involved in the metabolism and regulation of hormones. These results expand our understanding of the complex mechanisms involved in chilling tolerance in maize, and provide a set of candidate genes for further genetic analyses. | Jihua Mao Yongtao Yu Jing Yang Gaoke Li Chunyan Li Xitao Qi Tianxiang Wen Jianguang Hu | 2017 | The Crop Journal2017，5，5： | 2 |
| 4 | Atomic-level insight of sulfidation-engineered Aurivillius-related Bi_(2)O_(2)SiO_(3) nanosheets enabling visible light low-concentration CO_(2) conversion显示文摘Unraveling atomic-level active sites of layered photocatalyst towards lowconcentration CO_(2) conversion is still challenging.Herein,the yield and selectivity of photocatalytic CO_(2) reduction of the Aurivillius-related oxide semiconductor Bi_(2)O_(2)SiO_(3) nanosheet(BOSO)were largely improved using a surface sulfidation strategy.The experiment and theoretical calculation confirmed that surface sulfidation of the Bi_(2)O_(2)SiO_(3) nanosheet(S-BOSO,6.28 nm)redistributed the charge-enriched Bi sites,extended the solar spectrum absorption to the whole visible range,and considerably enhanced the charge separation,in addition to creating new reaction active sites,as compared to pristine BOSO.Subsequently,surface sulfidation played a switchable role,wherein S-BOSO showed a very high CH_(3)OH generation rate(12.78μmol g^(-1) for 4 h,78.6%selectivity)from low-concentration CO_(2)(1000 ppm)under visible light irradiation,which outperforms most of the state-of-the-art photocatalysts under similar conditions.This study presents an atomic-level modification protocol for engineering reactive sites and charge behaviors to promote solar-to-energy conversion. | Kai Wang Yue Du Yuan Li Xiaoyong Wu Haiyan Hu Guohong Wang Yao Xiao Shulei Chou Gaoke Zhang | 2023 | Carbon Energy2023，5，2： | 2 |
| 5 | Condensation of eigen microstate in statistical ensemble and phase transition显示文摘In a statistical ensemble with M microstates, we introduce an M × M correlation matrix with correlations among microstates as its elements. Eigen microstates of ensemble can be defined using eigenvectors of the correlation matrix. The eigenvalue normalized by M represents weight factor in the ensemble of the corresponding eigen microstate. In the limit M →∞, weight factors drop to zero in the ensemble without localization of the microstate. The finite limit of the weight factor when M →∞ indicates a condensation of the corresponding eigen microstate. This finding indicates a transition into a new phase characterized by the condensed eigen microstate. We propose a finite-size scaling relation of weight factors near critical point, which can be used to identify the phase transition and its universality class of general complex systems. The condensation of eigen microstate and the finite-size scaling relation of weight factors are confirmed using Monte Carlo data of one-dimensional and two-dimensional Ising models. | GaoKe Hu Teng Liu MaoXin Liu Wei Chen XiaoSong Chen | 2019 | Science China(Physics,Mechanics & Astronomy)2019，62，9： | 2 |
| 6 | Universality class of machine learning for critical phenomena显示文摘Herein,percolation phase transitions on a two-dimensional lattice were studied using machine learning techniques.Results reveal that different phase transitions belonging to the same universality class can be identified using the same neural networks(NNs),whereas phase transitions of different universality classes require different NNs.Based on this finding,we proposed the universality class of machine learning for critical phenomena.Furthermore,we investigated and discussed the NNs of different universality classes.Our research contributes to machine learning by relating the NNs with the universality class. | Gaoke Hu Yu Sun Teng Liu Yongwen Zhang Maoxin Liu Jingfang Fan Wei Chen Xiaosong Chen | 2023 | Science China(Physics,Mechanics & Astronomy)2023，66，12： | 0 |
| 7 | Study of the shear-rate dependence of granular friction based on community detection显示文摘In this study, computer simulations are performed on three-dimensional granular systems under shear conditions. The system comprises granular particles that are confined between two rigid plates. The top plate is subjected to a normal force and driven by a shearing velocity. A positive shear-rate dependence of granular friction, known as velocity-strengthening, exists between the granular and shearing plate. To understand the origin of the dependence of frictional sliding, we treat the granular system as a complex network, where granular particles are nodes and normal contact forces are weighted edges used to obtain insight into the interiors of granular matter. Community structures within granular property networks are detected under different shearing velocities in the steady state. Community parameters, such as the size of the largest cluster and average size of clusters, show significant monotonous trends in shearing velocity associated with the shear-rate dependence of granular friction. Then, we apply an instantaneous change in shearing velocity. A dramatic increase in friction is observed with a change in shearing velocity in the non-steady state. The community structures in the non-steady state are different from those in the steady state. Results indicate that the largest cluster is a key factor affecting the friction between the granular and shearing plate. | YongWen Zhang GaoKe Hu XiaoSong Chen Wei Chen WenQi Liu | 2019 | Science China(Physics,Mechanics & Astronomy)2019，62，4： | 0 |
| 8 | Finite-size scaling of correlation functions in finite systems显示文摘We propose the finite-size scaling of correlation functions in finite systems near their critical points.At a distance r in a ddimensional finite system of size L,the correlation function can be written as the product of|r|^(-(d-2+η))and a finite-size scaling function of the variables r/L and tL^(1/ν),where t=(T-T_c)/T_c,ηis the critical exponent of correlation function,andνis the critical exponent of correlation length.The correlation function only has a sigificant directional dependence when|r|is compariable to L.We then confirm this finite-size scaling by calculating the correlation functions of the two-dimensional Ising model and the bond percolation in two-dimensional lattices using Monte Carlo simulations.We can use the finite-size scaling of the correlation function to determine the critical point and the critical exponentη. | Xin Zhang GaoKe Hu YongWen Zhang XiaoTeng Li XiaoSong Chen | 2018 | Science China(Physics,Mechanics & Astronomy)2018，61，12： | 0 |
| 9 | Unpacking the black box of deep learning for identifying El Nino-Southern oscillation显示文摘By training a convolutional neural network(CNN) model, we successfully recognize different phases of the El Nino-Southern oscillation. Our model achieves high recognition performance,with accuracy rates of 89.4% for the training dataset and 86.4% for the validation dataset.Through statistical analysis of the weight parameter distribution and activation output in the CNN, we find that most of the convolution kernels and hidden layer neurons remain inactive,while only two convolution kernels and two hidden layer neurons play active roles. By examining the weight parameters of connections between the active convolution kernels and the active hidden neurons, we can automatically differentiate various types of El Nino and La Nina,thereby identifying the specific functions of each part of the CNN. We anticipate that this progress will be helpful for future studies on both climate prediction and a deeper understanding of artificial neural networks. | Yu Sun Yusupjan Habibulla Gaoke Hu Jun Meng Zhenghui Lu Maoxin Liu Xiaosong Chen | 2023 | Communications in Theoretical Physics2023，75，9： | 0 |
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