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国际医学放射学杂志 2017年第5期 619-619页

作者： C.Wu G.B.Wang Y.x.zhao W.Hao l.x.zhao x.J.Zhang 胡现宁 Department of MR Shandong Medical Imaging Research InstituteShandong University

摘要目的确定扩散张量成像(DTI)诊断糖尿病周围神经病变(DPN)的准确性和观察者之间的关系,并探讨其与电生理学的相关性。方法纳入的12例健康志愿者(对照组)和

关键词：扩散张量 DTI DPN 相关性糖尿病周围神经病变腓总神经胫神经

IDSSCNN-xgBoost:Improved Dual-Stream Shallow Convolutional Neural Network Based on Extreme Gradient Boosting Algorithm for Micro Expression Recognition

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Computers, Materials & Continua 2025年第1期82卷 729-749页

作者： Adnan Ahmad zhao li Irfan Tariq Zhengran He School of Information Science and Engineering Southeast UniversityNanjing210016China

Micro-expressions(ME)recognition is a complex task that requires advanced techniques to extract informative features fromfacial *** deep neural networks(DNNs)with convolutional structures have been ***,unlike DNNs,shallow convolutional neural networks often outperform deeper models in mitigating overfitting,particularly with small ***,many of these methods rely on a single feature for recognition,resulting in an insufficient ability to extract highly effective *** address this limitation,in this paper,an Improved Dual-stream Shallow Convolutional Neural Network based on an Extreme Gradient Boosting Algorithm(IDSSCNN-xgBoost)is introduced for ME *** proposed method utilizes a dual-stream architecture where motion vectors(temporal features)are extracted using Optical Flow TV-l1 and amplify subtle changes(spatial features)via EulerianVideoMagnification(EVM).These features are processed by IDSSCNN,with an attention mechanism applied to refine the extracted effective *** outputs are then fused,concatenated,and classified using the xgBoost *** comprehensive approach significantly improves recognition accuracy by leveraging the strengths of both temporal and spatial information,supported by the robust classification power of *** proposed method is evaluated on three publicly available ME databases named Chinese Academy of Sciences Micro-expression Database(CASMEII),Spontaneous Micro-Expression Database(SMICHS),and Spontaneous Actions and Micro-Movements(SAMM).Experimental results indicate that the proposed model can achieve outstanding results compared to recent *** accuracy results are 79.01%,69.22%,and 68.99%on CASMEII,SMIC-HS,and SAMM,and the F1-score are 75.47%,68.91%,and 63.84%,*** proposed method has the advantage of operational efficiency and less computational time.

关键词： ME recognition dual stream shallow convolutional neural network euler video magnification TV-l1 xgBoost

low-cost and fluoride-free synthesis of MFI zeolite nanosheets with enhanced stability for benzene alkylation with ethanol

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Journal of Energy Chemistry 2025年第1期100卷 458-468页

作者： Peng Zhu Cun liu Yiren Yu Guoshu Gao Yumeng zhao xiongfu Zhang Guodong liu Guohui Yang State Key laboratory of Fine Chemicals School of Chemical Engineering Dalian University of Technology State Key laboratory of Catalysis Dalian Institute of Chemical Physics Chinese Academy of Sciences

Zeolite nanosheets with a short b-axis thickness are highly desirable in lots of catalytic reactions due to their reduced diffusion resistance. Nevertheless, conventional synthesis methods usually require expensive structure-directing agents(SDAs), pricey raw materials, and eco-unfriendly fluorine-containing additives. Here, we contributed a cost-effective and fluoride-free synthesis method for synthesizing high-quality MFI zeolite nanosheets through a Silicalite-1(Sil-1) seed suspension and urea cooperative strategy, only with inexpensive colloidal silica as the Si source. Our approach was effective for synthesizing both Sil-1 and aluminum-containing ZSM-5 nanosheets. By optimizing key synthesis parameters,including seed aging time, seed quantity, and urea concentration, we achieved precise control over the crystal face aspect ratio and b-axis thickness. We also revealed a non-classical oriented nanosheet growth mechanism, where Sil-1 seeds induced the formation of quasi-ordered precursor particles, and the(010)crystal planes of these particles facilitated urea adsorption, thereby promoting c-axis-oriented *** obtained ZSM-5 nanosheets exhibited exceptional catalytic performance in the benzene alkylation with ethanol, maintaining stability for over 500 h, which is 5 times longer than traditional ZSM-5 catalysts. Furthermore, large-scale production of ZSM-5 nanosheets was successfully carried out in a 3 l highpressure autoclave, yielding samples consistent with those from laboratory-scale synthesis. This work marks a significant step forward in the sustainable and efficient production of MFI nanosheets using inexpensive and environmentally friendly raw materials, offering the broad applicability in catalysis.

关键词： Aspect ratio

Wenchuan Post-earthquake Reconstruction by Utilizing Composite Tubular Construction and FRP Retrofitting Technology

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四川大学学报（工程科学版） 2009年第3期41卷 231-247页

作者： zhao x l Al-MAHAIDI R Dept. of Civil Eng. Monash Univ. Clayton VIC 3800 Australia

This paper presents two possible construction methods that could be adopted in the Wenchuan post-earthquake *** is the composite tubular construction and the other is FRP(Fibre Reinforced Polymer) retrofitting *** background of these two methods,the existing research and relevance to Whenchuan post-earthquake reconstruction are described.

关键词：抗振结构建筑结构建筑物 FRP 地震重建

Seasonal dependency of controlling factors on the phytoplankton production in Taihu lake, China

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Journal of Environmental Sciences 2019年第2期31卷 278-288页

作者： Qiaohua zhao Jing Wang Jianjian Wang Julian x.l.Wang College of Hydrometeorology Nanjing University of Information Science and Technology Air Resources laboratory National Oceanic and Atmospheric AdministrationCollege Park

In this study, 44 profiles of gross primary productivity(GPP) and sunlight, along with water temperature, Chlorophyll-a(Chla) and nutrients, were observed in Meiliang Bay of Taihu lake, China, in the spring, summer, and fall seasons. Effects of water temperature, light,and nutrient concentration were examined in relation to the GPP-unit-Chla(GPP of algae per Chla). The results showed that the optimum temperature for the GPP of phytoplankton was 27.9°C, the optimal PNA-unit-Chla(photon number absorbed by phytoplankton per Chla) was 0.25(mol), and the HSCN-unit-Chla and HSCP-unit-Chla(half-saturation constants of nitrogen and phosphorus of algae per Chla) were 0.005(mg/l) and 0.0004(mg/l), respectively. The seasonal dependency of the effect of different factors on the GPP was analyzed. Compared with temperature and nutrients, light was found to be the most important factor affecting the GPP during the three seasons. The effect of temperature and nutrients on the GPP of phytoplankton has obvious seasonal change. In spring, temperature was the secondary factor affecting the GPP of phytoplankton, and the effect of nutrients may be negligible in the eutrophic lake on account of temperature limit, which showed that the GPP of algae was only affected by the physical process. In summer and fall, temperature didn't affect the GPP of algae, and the presence of nutrients was the secondary factor affecting the GPP of phytoplankton. From summer to fall, effect of phosphorus was weakened and effect of nitrogen was enhanced.

关键词： Temperature limited effect Gross primary productivity Eutrophication light limit Optimum temperature Half-saturation constants

EFFECT OF SIlICON ADDITION ON RECRYSTAllIZATION AND PHASE TRANSFORMATION BEHAVIOR OF HIGH-STRENGTH HOT-ROllED TRIP STEEl

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Acta Metallurgica Sinica(English letters) 2008年第3期21卷 163-168页

作者： l.J. Zhu D. Wu x.M. zhao College of Materials Science and Engineering Jilin University Changchun 130025 China The State Key laboratory of Rolling Technology and Automation Northeastern University Shenyang110004 China

Because Si is a noncarbide forming element, a multiphase microstructure consisting of ferrite, bainite, and retained austenite, at room temperature, can be formed by controlling the thermomechanical process strictly. The cooling schedules must be restricted by the formation of pearlite and cementite. In the present article, a new integrated mathematical model for prediction of microstructure evolution during controlled rolling and controlled cooling is developed for a typical kind of low carbon Si-Mn TRIP steel, which consists of temperature simulation, recrystallization, and transformation models. The influence of Si contents has been thoroughly investigated. The calculated results indicate that Si retards recrystallization, restrains austenite grain growth as well as accelerates polygonal ferrite transformation.

关键词： TRIP steel Recrystallization Ferrite transformation Bainite transformation Silicon

Stress-Induced Martensitic Transformation of Zr_(50)Cu_(25)Ni_(10)Co_(15) Nanocrystals Embedded in an Amorphous Matrix

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Journal of Materials Science & Technology 2017年第3期33卷 276-280页

作者： W.H.Gao x.Y.Yi x.l.Meng G.Song W.Cai l.C.zhao School of Materials Science and Engineering Harbin Institute of Technology Department of Mechanical Engineering University of Houston

The stress induced martensitic phase transformation of spherical ZrCu nanocrystals embedded in an amorphous matrix was studied in this paper. Microstructural observations revealed that the martensitic transformation of the nanocrystal was hindered by the surrounding amorphous coating. The existence of two-step transformation from the austenite phase（B2） to the base structure martensite（B19＇） and finally to the most stable superstructure martensite（Cm） was also demonstrated. The Cm martensite with（021） type I twinning symmetrically accommodation was surrounded by the B19＇ martensite with dislocation morphologies.

关键词： Nanocrystals ZrCu Martensitic phase transformation Shape memory Transmission electron microscopy

Machine learning guided automatic recognition of crystal boundaries in bainitic/martensitic alloy and relationship between boundary types and ductile-to-brittle transition behavior

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Journal of Materials Science & Technology 2021年第25期84卷 49-58页

作者： x.C.li J.x.zhao J.H.Cong R.D.K.Misra x.M.Wang x.l.Wang C.J.Shang Collaborative Innovation Center of Steel Technology University of Science and Technology BeijingBeijing 100083China Department of Metallurgical Materials and Biomedical EngineeringUniversity of Texas at El Paso500 W.University AvenueEl PasoTX 79968USA

Gradient boosting decision tree(GBDT)machine learning(Ml)method was adopted for the first time to automatically recognize and conduct quantitative statistical analysis of boundaries in bainitic microstructure using electron back-scatter diffraction(EBSD)*** spite of lack of large sets of EBSD data,we were successful in achieving the desired accuracy and accomplishing the objective of recognizing the *** with a low model accuracy ofler angles or axis-angle pair as characteristic features,the accuracy of the model was significantly enhanced to about 88%when the Euler angle was converted to overall misorientation angle(OMA)and specific misorientation angle(SMA)and considered as important *** this model,the recall score of prior austenite grain(PAG)boundary was~93%,high angle packet boundary(OMA>40°)was~97%,and block boundary was~96%.The derived outcomes of Ml were used to obtain insights into the ductile-to-brittle transition(DBTT)***,Ml modeling approach suggested that DBTT was not determined by the density of high angle grain boundaries,but significantly influenced by the density of PAG and packet *** study underscores that Ml has a great potential in detailed recognition of complex multi-hierarchical microstructure such as bainite and martensite and relates to material performance.

关键词： Machine learning Feature engineering Automatic recognition lath structure Crystallography

Dynamic mechanical properties,deformation and damage mechanisms of eutectic high-entropy alloy AlCoCrFeNi_(2.1)under plate impact

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Journal of Materials Science & Technology 2023年第3期134卷 178-188页

作者： S.P.zhao Z.D.Feng l.x.li x.J.zhao l.lu S.Chen N.B.Zhang Y.Cai S.N.luo The Peac Institute of Multiscale Sciences ChengduChina Key laboratory of Advanced Technologies of Materials Ministry of EducationSouthwest Jiaotong UniversityChengduChina

Shock compression and spallation of a eutectic high-entropy alloy(HEA)AlCoCrFeNi_(2.1)with lamellar structure are investigated via plate impact loading with free-surface velocity *** as-cast and postmortem samples are characterized with transmission electron microscopy,electron back-scatter diffraction and scanning electron *** accurate Hugoniot equation of state is ***-ter shock compression to∼12 GPa,both the l1_(2)and B_(2)phases retain their ordered *** dislocations in the{111}slip planes,stacking faults and deformation twins are found in the l1_(2)phase,along with fewer dislocations in the{110}slip bands in the B(2)***-induced deformation twin-ning within the l1_(2)phase of this HEA is observed as a new deformation mechanism under various load-ing *** spallation,both ductile and brittle damage modes are *** micro voids and cracks prefer to nucleate at the phase boundaries chiefly,then in the B(2)*** similar shock stress,the spall strength of AlCoCrFeNi_(2.1)HEA is about 40%higher than those of other reported dual-phase HEAs due to the high stability of its semi-coherent phase boundaries.

关键词： High-entropy alloy Hugoniot Spall damage Microstructure