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Internal dynamics of magma ocean and its linkage to atmospheres

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Acta Geochimica 2022年第4期41卷 568-591页

作者： yizhuo zhang Nan zhang Meng Tian Key Laboratory of Orogenic Belts and Crustal Evolution School of Earth and Space SciencesPeking UniversityBeijing100871China Earth Dynamics Research Group School of Earth and Planetary SciencesCurtin UniversityBentley6102WAAustralia Center for Space and Habitability Universität BernGesellschaftsstrasse 63012BernSwitzerland

Geological and astronomical observations on the‘‘lava world’’of the rocky planet,with additional theoretical interpretation of Moon’s crustal formation,bring up to the occurrence of the magma ocean and lava ponds,which inherits accretion energy of rocky planetesimal and evolves with subsequent energy *** or global oceans of silicate melt could be a widespread lava phase after rocky planet accretion as well as large impact and could persist on planets on orbits around other stars for various time *** processes of magma ocean formation and solidification change the phases,cause element segregations,and strongly affect the earliest compositional differentiation and volatile content of the terrestrial *** form the starting point for cooling to mildly habitable conditions and for the onset of thermally driven solid-state mantle *** formation and crystallization of magma oceans also influence the assembly of a core,the origin of a crust,initiation of tectonics,and formation of an *** is inevitable to investigate the magma ocean dynamics of such an early period of Earth *** review focuses on the internal dynamics of magma oceans after planetesimal accretion and planetary formation including turbulence,particle motion,and solid-state convection,which determine the associated processes of cooling,crystallization,and convection of magma *** differentiation is discussed *** thermodynamics of equilibration between a magma ocean and an overlying,outgassed atmosphere is also discussed,highlighting the need for more data on volatile solubility in silicate *** effect of coupling between magma ocean and solid-state mantle convection is also discussed.

关键词： Magma ocean Early atmosphere Internal dynamics

A novel image segmentation approach for wood plate surface defect classification through convex optimization

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Journal of Forestry Research 2018年第6期29卷 1789-1795页

作者： Zhanyuan Chang Jun Cao yizhuo zhang College of Mechanical and Electrical Engineering Northeast Forestry University College of Information Mechanical and Electrical EngineeringShanghai Normal University

Detection of wood plate surface defects using image processing is a complicated problem in the forest industry as the image of the wood surface contains different kinds of defects. In order to obtain complete defect images, we used convex optimization(CO) with different weights as a pretreatment method for smoothing and the Otsu segmentation method to obtain the target defect area images. Structural similarity(SSIM) results between original image and defect image were calculated to evaluate the performance of segmentation with different convex optimization weights. The geometric and intensity features of defects were extracted before constructing a classification and regression tree(CART) classifier. The average accuracy of the classifier is 94.1% with four types of defects on Xylosma congestum wood plate surface: pinhole, crack,live knot and dead knot. Experimental results showed that CO can save the edge of target defects maximally, SSIM can select the appropriate weight for CO, and the CART classifier appears to have the advantages of good adaptability and high classification accuracy.

关键词： Convex optimization Threshold segmentation Structure similarity Decision tree Defect recognition

Mechanical properties of wood materials using near-infrared spectroscopy based on correlation local embedding and partial least-squares

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Journal of Forestry Research 2020年第3期31卷 1053-1060页

作者： Lei Yu Yuliang Liang yizhuo zhang Jun Cao Mechanical and Electrical College Northeast Forestry UniversityHarbin 150040People’s Republic of China

This study used near-infrared(NIR)spectroscopy to predict mechanical properties of *** spectra were collected in wavelengths 900–1700 nm,and spectra averaged by radial and tangential surface spectra were used to establish a partial least square(PLS)model based on correlation local embedding(CLE).Mongolian oak(Quercus mongolica *** Ledeb.)was used to test the eff ectiveness of the *** cross-validation method was used to verify the robustness of the CLE–PLS *** samples were tested as the calibration set and forty-fi ve as the validation *** results show that the prediction coeffi cient of determination(R2 p)is 0.80 for MOR,and 0.78 for *** ratio of performance to deviation is 2.23 for MOR and 2.15 for MOE.

关键词： Modulus of rupture Modulus of elasticity Near-infrared Correlation local embedding Partial least square

Root imaging from ground penetrating radar data by CPSO-OMP compressed sensing

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Journal of Forestry Research 2017年第1期28卷 155-162页

作者： Chao Li Yaowen Su yizhuo zhang Huimin Yang Northeast Forestry University Harbin 150040People's Republic of China

As the amount of data produced by ground penetrating radar （GPR） for roots is large, the transmission and the storage of data consumes great resources. To alleviate this problem, we propose here a root imaging algorithm using chaotic particle swarm optimal （CPSO） compressed sensing based on GPR data according to the sparsity of root space. Radar data are decomposed, observed, measured and represented in sparse manner, so roots image can be reconstructed with limited data. Firstly, radar signal measurement and sparse representation are implemented, and the solution space is established by wavelet basis and Gauss random matrix; secondly, the matching function is considered as the fitness function, and the best fitness value is found by a PSO algorithm; then, a chaotic search was used to obtain the global optimal operator; finally, the root image is reconstructed by the optimal operators. A-scan data, B-scan data, and complex data from American GSSI GPR is used, respectively, in the experimental test. For B-scan data, the computation time was reduced 60 % and PSNR was improved 5.539 dB; for actual root data imaging, the reconstruction PSNR was 26.300 dB, and total computation time was only 67.210 s. The CPSO-OMP algorithm overcomes the problem of local optimum trapping and comprehensively enhances the precision during reconstruction.

关键词： Chaotic particle swarm Compression sensing Ground penetrating radar Orthogonal matching pursuit (OMP) Root imaging

A novel NIRS modelling method with OPLS-SPA and MIX-PLS for timber evaluation

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Journal of Forestry Research 2022年第1期33卷 369-376页

作者： Jinhao Chen Huilig Yu Dapeng Jiang yizhuo zhang Keqi Wang College of Mechanical and Electrical Engineering Northeast Forestry UniversityHarbin 150040People’s Republic of China College of Information and Computer Engineering Northeast Forestry UniversityHarbin 150040People’s Republic of China

The identification of timber properties is important for safe *** Infrared Spectroscopy(NIRS)technology is widely-used because of its simplicity,efficiency,and positive environmental ***,in its application,weak signals are extracted from complex,overlapping and changing *** study focused on the stability of NIR *** Orthogonal Partial Least Squares(OPLS)and Successive Projections Algorithm(SPA)eliminates noise and extracts effective spectra,and an ensemble learning method MIX-PLS,is applied to establish the *** elastic modulus of timber is taken as an example,and 201 wood samples of three species,Xylosmacongesta(Lour.)Merr.,Acer pictum ***,and Betula pendula,samples were divided into three groups to investigate modelling *** results show that OPLS can preprocess the near-infrared spectroscopy information according to the target object in the face of the system error and reduce errors to *** finally selects 13 spectral bands,simplifies the NIR spectral data and improves model *** Pearson's correlation coefficient of Calibration(Rc)and the Pearson's correlation coefficient of Prediction(Rp)of Mix Partial Least Squares(MIX-PLS)were 0.95 and 0.90,and Root Mean Square Error of Calibration(RMSEC)and Root Mean Square Error of Prediction(RMSEP)are 2.075 and 6.001,respectively,which shows the model has good generalization abilities.

关键词： NIR prediction Orthogonal partial least squares(OPLS) Successive projections algorithm(SPA) Mix partial least squares(MIX-PLS)modulus of elasticity

Current therapeutic landscape and resistance mechanisms to larotrectinib

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Cancer Biology & Medicine 2023年第12期20卷 967-971页

作者： Weiji Xie Jiaqian Xu Suying Lu yizhuo zhang Department of Pediatric Oncology State Key Laboratory of Oncology in South ChinaGuangdong Provincial Clinical Research Center for CancerCollaborative Innovation Center for Cancer MedicineSun Yat-sen University Cancer CenterGuangzhou 510060China Young Talents Program of Sun Yat-sen University Cancer Center Guangzhou 510060China

Cancer has emerged as the leading cause of mortality worldwide and is driven by numerous intricate *** tropomyosin receptor kinase (TRK) proto-oncogene family consists of the TRKA,TRKB,and TRKC transmembrane receptors,which are encoded by the NTRK1,NTRK2,and NTRK3 genes,respectively,and are widely expressed in the nervous system and many non-neuronal tissue *** signaling plays crucial roles in neuronal development,differentiation,and diverse neuronal functions,such as neuronal survival,synapse formation and plasticity,and axon and dendrite formation,in physiologic processes3.

关键词： mortality Cancer landscape

Recognition of wood surface defects with near infrared spectroscopy and machine vision

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Journal of Forestry Research 2019年第6期30卷 2379-2386页

作者： Huiling Yu Yuliang Liang Hao Liang yizhuo zhang Northeast Forestry University

To improve the accuracy in recognizing defects on wood surfaces,a method fusing near infrared spectroscopy(NIR)and machine vision was *** gmelinii was selected as the raw material,and the experiments focused on the ability of the model to sort defects into four types:live knots,dead knots,pinholes,and *** images were taken using an industrial camera,and a morphological algorithm was applied to locate the position of the defects.A portable near infrared spectrometer(900–1800 nm)collected the spectra of these *** addition,principal component analysis was utilized on these variables from spectral information and principal component vectors were extracted as the inputs of the *** results show that a back propagation neural network model exhibited better discrimination accuracy of 92.7%for the training set and 92.0%for the test *** research reveals that the NIR fusing machine vision is a feasible tool for detecting defects on board surfaces.

关键词： Wood board surface defects Near infrared spectroscopy Machine vision Accuracy of recognition

Infrared Fault Detection Method for Dense Electrolytic Bath Polar Plate Based on YOLOv5s

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Computers, Materials & Continua 2024年第9期80卷 4859-4874页

作者： Huiling Yu Yanqiu Hang Shen Shi Kangning Wu yizhuo zhang Software Engineering Department of Computer ScienceChangzhou UniversityChangzhou213146China Electrical Engineering Department of Computer ScienceChangzhou UniversityChangzhou213146China

Electrolysis tanks are used to smeltmetals based on electrochemical principles,and the short-circuiting of the pole plates in the tanks in the production process will lead to high temperatures,thus affecting normal *** at the problems of time-consuming and poor accuracy of existing infrared methods for high-temperature detection of dense pole plates in electrolysis tanks,an infrared dense pole plate anomalous target detection network YOLOv5-RMF based on You Only Look Once version 5(YOLOv5)is ***,we modified the Real-Time Enhanced Super-Resolution Generative Adversarial Network(Real-ESRGAN)by changing the U-shaped network(U-Net)to Attention U-Net,to preprocess the images;secondly,we propose a new Focus module that introduces the Marr operator,which can provide more boundary information for the network;again,because Complete Intersection over Union(CIOU)cannot accommodate target borders that are increasing and decreasing,replace CIOU with Extended Intersection over Union(EIOU),while the loss function is changed to Focal and Efficient IOU(Focal-EIOU)due to the different difficulty of sample *** the homemade dataset,the precision of our method is 94%,the recall is 70.8%,and the map@.5 is 83.6%,which is an improvement of 1.3%in precision,9.7%in recall,and 7%in map@.5 over the original *** algorithm can meet the needs of electrolysis tank pole plate abnormal temperature detection,which can lay a technical foundation for improving production efficiency and reducing production waste.

关键词： Infrared polar plate fault detection YOLOv5 Real-ESRGAN Marr boundary detection operator Focal-EIoU loss

Wood defect detection method with PCA feature fusion and compressed sensing

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Journal of Forestry Research 2015年第3期26卷 745-751页

作者： yizhuo zhang Chao Xu Chao Li Huiling Yu Jun Cao Northeast Forestry University

We used principa/component analysis （PCA） and compressed sensing to detect wood defects from wood plate images. PCA makes it possible to reduce data redundancy and feature dimensions and compressed sensing, used as a elas- sifter, improves identification accuracy. We extracted 25 features, including geometry and regional features, gray-scale texture features, and invariant moment features, from wood board images and then integrated them using PCA, and se- lected eight principal components to express defects. After the fusion process, we used the features to construct a data dic- tionary, and realized the classification of defects by computing the optimal solution of the data dictionary in l1 norm using the least square method. We tested 50 Xylosma samples of live knots, dead knots, and cracks. The average detection time with PCA feature fusion and without were 0.2015 and 0.7125 ms, respectively. The original detection accuracy by SOM neural network was 87 %, but after compressed sensing, it was 92 %.

关键词： Principal component analysis Compressedsensing Wood board classification Defect detection