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Microstructure evolution of Ti_(48)Zr_(27)Cu_(6)Nb_(5)Be_(14)amorphous alloy after semi-solid isothermal treatment

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China Foundry 2024年第3期21卷 287-294页

作者： xin-hua Huang Jing-wen Pu Yong-xin luo Yue-jun Ouyang School of Material Electricity and Intelligent ManufacturingHuaihua UniversityHuaihua 330031HunanChina Hunan Renewable Aluminum Innovation Research Center Huaihua UniversityHuaihua 330031HunanChina

The as-cast amorphous Ti_(48)Zr_(27)Cu_(6)Nb_(5)Be_(14)composites,comprising in situ formedβ-Ti ductile crystalline precipitates,were prepared by water cooled copper mold suction casting.Then,the semi-solid composites were obtained after the as-cast composites were treated by semi-solid isothermal treatment.The microstructure evolution and kinetics of the composites were examined.Results show that the microstructures of both the as-cast and semi-solid composites comprise ofβ-Ti crystal phases and amorphous matrix phases.Before and after treatment,the crystals evolve from fine granular or fine dendritic crystals to coarse crystals.As the treatment temperature increasing or the time prolonging,the average crystal size gradually increases and the surface morphology of the crystals gradually becomes regular.By studying the microstructural evolution and dynamics during the isothermal treatment process,it is found that the final morphology ofβ-Ti crystals is influenced by the isothermal treatment temperature and time(t),and theβ-Ti evolution rate increases with an increase in treatment temperature.In addition,a linear relationship was observed between the size of cubicβ-Ti crystals(D^(3))and t;the growth kinetics factor K is 3.8μm^(3)·s^(-1).As the K value closes to 4μm^(3)·s^(-1),it is inferred the morphology evolution ofβ-Ti crystals is a coarsening behavior controlled by the diffusion of solute elements.

关键词： Ti_(48)Zr_(27)Cu_(6)Nb_(5)Be_(14) amorphous matrix composites semi-solid as-cast microstructure

Long-term Evolution of Solar Activity and Prediction of the Following Solar Cycles

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Research in Astronomy and Astrophysics 2024年第3期24卷 194-204页

作者： Pei-xin luo Bao-Lin Tan National Astronomical Observatories Chinese Academy of SciencesBeijing 100101China School of Astronomy and Space Science University of Chinese Academy of SciencesBeijing 100049China

Solar activities have a great impact on modern high-tech systems,such as human aerospace activities,satellite communication and navigation,deep space exploration,and related scientific research.Therefore,studying the long-term evolution trend of solar activity and accurately predicting the future solar cycles are highly anticipated.Based on the wavelet transform and empirical function fitting of the longest recorded data of the annual average relative sunspot number(ASN)series of 323 yr to date,this work decisively verifies the existence of the solar century cycles and confirms that its length is about 104.0 yr,and the magnitude has a slightly increasing trend on the timescale of several hundred years.Based on this long-term evolutionary trend,we predict solar cycles 25 and26 by using phase similar prediction methods.As for solar cycle 25,its maximum ASN will be about146.7±33.40,obviously stronger than solar cycle 24.The peak year will occur approximately in 2024,and the period will be about 11±1 yr.As for solar cycle 26,it will start around 2030,and reach its maximum between2035 and 2036,with maximum ASN of about 133.0±3.200,and period of about 10 yr.

关键词： Sun activity-Sun evolution-(Sun) sunspots-methods data analysis

Quick Weighing of Passing Vehicles Using the Transfer-Learning-Enhanced Convolutional Neural Network

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Computer Modeling in Engineering & Sciences 2024年第6期139卷 2507-2524页

作者： Wangchen Yan Jinbao Yang xin luo College of Civil Engineering Xiangtan UniversityXiangtan411105China Energy&Environmental Engineering Department China CEC Engineering CorporationChangsha410114China

Transfer learning could reduce the time and resources required by the training of new models and be therefore important for generalized applications of the trainedmachine learning algorithms.In this study,a transfer learningenhanced convolutional neural network(CNN)was proposed to identify the gross weight and the axle weight of moving vehicles on the bridge.The proposed transfer learning-enhanced CNN model was expected to weigh different bridges based on a small amount of training datasets and provide high identification accuracy.First of all,a CNN algorithm for bridge weigh-in-motion(B-WIM)technology was proposed to identify the axle weight and the gross weight of the typical two-axle,three-axle,and five-axle vehicles as they crossed the bridge with different loading routes and speeds.Then,the pre-trained CNN model was transferred by fine-tuning to weigh themoving vehicle on another bridge.Finally,the identification accuracy and the amount of training data required were compared between the two CNN models.Results showed that the pre-trained CNN model using transfer learning for B-WIM technology could be successfully used for the identification of the axle weight and the gross weight for moving vehicles on another bridge while reducing the training data by 63%.Moreover,the recognition accuracy of the pre-trained CNN model using transfer learning was comparable to that of the original model,showing its promising potentials in the actual applications.

关键词： Bridge weigh-in-motion transfer learning convolutional neural network

A Novel Tensor Decomposition-Based Efficient Detector for Low-Altitude Aerial Objects With Knowledge Distillation Scheme

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IEEE/CAA Journal of Automatica Sinica 2024年第2期11卷 487-501页

作者： Nianyin Zeng xinyu Li Peishu Wu Han Li xin luo Department of Instrumental and Electrical Engineering Xiamen UniversityXiamen 361005China IEEE College of Computer and Information Science Southwest UniversityChongqing 400715China

Unmanned aerial vehicles(UAVs) have gained significant attention in practical applications, especially the low-altitude aerial(LAA) object detection imposes stringent requirements on recognition accuracy and computational resources. In this paper, the LAA images-oriented tensor decomposition and knowledge distillation-based network(TDKD-Net) is proposed,where the TT-format TD(tensor decomposition) and equalweighted response-based KD(knowledge distillation) methods are designed to minimize redundant parameters while ensuring comparable performance. Moreover, some robust network structures are developed, including the small object detection head and the dual-domain attention mechanism, which enable the model to leverage the learned knowledge from small-scale targets and selectively focus on salient features. Considering the imbalance of bounding box regression samples and the inaccuracy of regression geometric factors, the focal and efficient IoU(intersection of union) loss with optimal transport assignment(F-EIoU-OTA)mechanism is proposed to improve the detection accuracy. The proposed TDKD-Net is comprehensively evaluated through extensive experiments, and the results have demonstrated the effectiveness and superiority of the developed methods in comparison to other advanced detection algorithms, which also present high generalization and strong robustness. As a resource-efficient precise network, the complex detection of small and occluded LAA objects is also well addressed by TDKD-Net, which provides useful insights on handling imbalanced issues and realizing domain adaptation.

关键词： Attention mechanism knowledge distillation(KD) object detection tensor decomposition(TD) unmanned aerial vehicles(UAVs)

Generalized Embedding Machines for Recommender Systems

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Machine Intelligence Research 2024年第3期21卷 571-584页

作者： Enneng Yang xin xin Li Shen Yudong luo Guibing Guo Software College Northeastern UniversityShenyang110000China School of Computer Science and Technology Shandong UniversityQingdao266000China JD Explore Academy JD Explore AcademyBeijing100000China

Factorization machine (FM) is an effective model for feature-based recommendation that utilizes inner products to capture second-order feature interactions. However, one of the major drawbacks of FM is that it cannot capture complex high-order interaction signals. A common solution is to change the interaction function, such as stacking deep neural networks on the top level of FM. In this work, we propose an alternative approach to model high-order interaction signals at the embedding level, namely generalized embedding machine (GEM). The embedding used in GEM encodes not only the information from the feature itself but also the information from other correlated features. Under such a situation, the embedding becomes high-order. Then we can incorporate GEM with FM and even its advanced variants to perform feature interactions. More specifically, in this paper, we utilize graph convolution networks (GCN) to generate high-order embeddings. We integrate GEM with several FM-based models and conduct extensive experiments on two real-world datasets. The results demonstrate significant improvement of GEM over the corresponding baselines.

关键词： Feature interactions high-order interaction factorization machine(FM) recommender system graph neural network(GNN).

Effect of solvent on the initiation mechanism of living anionic polymerization of styrene:A computational study

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Chinese Journal of Chemical Engineering 2024年第5期69卷 135-142页

作者： Shen Li Yin-Ning Zhou Zhong-xin Liu Zheng-Hong luo School of Chemical Engineering and Technology Hainan UniversityHaikou 570228China Department of Chemical Engineering School of Chemistry and Chemical EngineeringState Key Laboratory of Metal Matrix CompositesShanghai Jiao Tong UniversityShanghai 200240China

For living anionic polymerization(LAP),solvent has a great influence on both reaction mechanism and kinetics.In this work,by using the classical butyl lithium-styrene polymerization as a model system,the effect of solvent on the mechanism and kinetics of LAP was revealed through a strategy combining density functional theory(DFT)calculations and kinetic modeling.In terms of mechanism,it is found that the stronger the solvent polarity,the more electrons transfer from initiator to solvent through detailed energy decomposition analysis of electrostatic interactions between initiator and solvent molecules.Furthermore,we also found that the stronger the solvent polarity,the higher the monomer initiation energy barrier and the smaller the initiation rate coefficient.Counterintuitively,initiation is more favorable at lower temperatures based on the calculated results ofΔG_(TS).Finally,the kinetic characteristics in different solvents were further examined by kinetic modeling.It is found that in benzene and n-pentane,the polymerization rate exhibits first-order kinetics.While,slow initiation and fast propagation were observed in tetrahydrofuran(THF)due to the slow free ion formation rate,leading to a deviation from first-order kinetics.

关键词： Living anionic polymerization Solvent effect Reaction kinetics Computational chemistry Mathematical modeling Kinetic modeling

Jurassic integrative stratigraphy,biotas,and paleogeographical evolution of the Qinghai-Tibetan Plateau and its surrounding areas

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Science China Earth Sciences 2024年第4期67卷 1195-1228页

作者： Jianguo LI xin RAO Lin MU Xiaohui CUI xin LI Hui luo Peixue LIU Center for Excellence in Life and Paleoenvironment Nanjing Institute of Geology and PalaeontologyChinese Academy of SciencesNanjing 210008China Nanjing College University of Chinese Academy of SciencesNanjing 211135China

The Qinghai-Tibetan Plateau experienced a unique geological evolution during the Jurassic,driven by the termination of the Palaeotethys and the reduction of the Neotethys.The Indian Plate separated from the northern margin of Gondwana and drifted northward from the Southern Hemisphere.Given that the timing of strata serves as the basis for reconstructing geological history,the present work aimed to develop a new multiple stratigraphic and chronologic framework for the Jurassic strata of the Qinghai-Tibetan Plateau region via a synthesis of the material on lithostratigraphy,palaeontology,iso-radiometric dating,magnetostratigraphy,and other techniques with an emphasis on recent progress and findings.The new framework included the Jurassic System from the four major subdivisions of the plateau:the Baryan Har,Qiangtang,Lhasa-Gandise,and Southern Xizang(Himalaya).Ultimately,a more complete,refined biostratigraphic sequence was proposed,comprising the most common fossils in the plateau and those that are stratigraphically significant for the Jurassic stratigraphy,including ammonites,bivalves,brachiopods,foraminifera,radiolarians,and dinoflagellate cysts for the marine strata,and pollen and spores,and charophytes for the terrestrial sediments.This biostratigraphic framework was correlated with the Jurassic international standard zonation of the Geological Time Scale 2020 via standard or representative species or genera of ammonites.Based on this framework,we constructed a lateral correlation of the Jurassic strata between different basins of the plateau.The palaeontologic correlation in the present work shows that the Lhasa-Gandise Block had a closer relationship with the Qiangtang Block than with the Southern Xizang Himalaya during the Jurassic Period.Meanwhile,the Lhasa-Gandise Block and Qiangtang Block shared similar marine fauna features of the north marginal East Tethys.This contrasts the opinion suggesting that the Yarlung Zangbo Tethys was a small back-arc basin.A combination of stratigraphical,palaeontological,a

关键词： Biostratigraphy Chronostratigraphy Correlation Yarlung Zangbo suture Bangong Co-Nujiang suture Tethys

Exogenous insulin autoimmune syndrome:A case report and review of literature

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World Journal of Clinical Cases 2024年第9期12卷 1691-1697页

作者： Ling-Ling Xu Jia-xin Chen Jing-Ping Cheng Ni luo Medical College School of MedicineWuhan University of Science and TechnologyWuhan 430065Hubei ProvinceChina Department of Gerontology CR&WISCO General Hospital Affiliated to Wuhan University of Science and TechnologyWuhan 430080Hubei ProvinceChina

BACKGROUND Insulin autoimmune syndrome(IAS)is a severe manifestation of spontaneous hypoglycemia.It is characterized by elevated levels of immune-reactive insulin and highly potent insulin autoantibodies(IAAs),which are induced by endogenous insulin circulating in the bloodstream.It is distinguished by recurring instances of spontaneous hypoglycemia,the presence of IAA within the body,a substantial elevation in serum insulin levels,and an absence of prior exogenous insulin administration.Nevertheless,recent studies show that both conventional insulin and its analogs can induce IAS episodes,giving rise to the notion of nonclassical IAS.Therefore,more attention should be paid to these diseases.CASE SUMMARY In this case report,we present a rare case of non-classical IAS in an 83-year-old male patient who present with symptoms of a psychiatric disorder.Upon symptom onset,the patient exhibited Whipple's triad(including hypoglycemia,blood glucose level less than 2.8 mmol/L during onset,and rapid relief of hypoglycemic symptoms after glucose administration).Concurrently,his serum insulin level was significantly elevated,which contradicted his C-peptide levels.After a comprehensive examination,the patient was diagnosed with exogenous insulin autoimmune syndrome.Considering that the patient had type 2 diabetes mellitus and a history of exogenous insulin use before disease onset,it was presumed that non classical IAS was induced by this condition.The PubMed database was used to search for previous cases of IAS and non-classical IAS to analyze their characteristics and treatment approaches.CONCLUSION The occurrence of non-classical IAS is associated with exogenous insulin or its analogs,as well as with sulfhydryl drugs.Symptoms can be effectively alleviated through the discontinuation of relevant medications,administration of hormones or immunosuppressants,plasma exchange,and lifestyle adjustments.

关键词： Insulin autoimmune syndrome Type 2 diabetes Exogenous insulin Insulin autoantibodies Hypoglycemia Case report

MFCC based real-time speech reproduction and recognition using distributed acoustic sensing technology

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Optoelectronics Letters 2024年第4期20卷 222-227页

作者： ZHOU Ran ZHAO Shuai luo Mingming MENG xin MA Jie LIU Jianfei School of Electronic Information Engineering Hebei University of TechnologyTianjin 300401China Tianjin Key Laboratory of Electronic Materials and Devices Hebei University of TechnologyTianjin 300401China Hebei Key Laboratory of Advanced Laser Technology and Equipment Hebei University of TechnologyTianjin 300401China

The distributed acoustic sensing technology was used for real-time speech reproduction and recognition,in which the voiceprint can be extracted by the Mel frequency cepstral coefficient(MFCC)method.A classic ancient Chinese poem“You Zi Yin”,also called“A Traveler’s Song”,was analyzed both in time and frequency domains,where its real-time reproduction was achieved with a 116.91 ms time delay.The smaller scaled MFCC0 at 1/12 of MFCC matrix was taken as a feature vector of each line against the ambient noise,which provides a recognition method via cross-correlation among the 6 original and recovered verse pairs.The averaged cross-correlation coefficient of the matching pairs is calculated to be 0.5806 higher than 0.1883 of the nonmatched pairs,promising an accurate and fast method for real-time speech reproduction and recognition over a passive optical fiber.

关键词： MFCC passive coefficient