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Inhibiting MMP13 Attenuates Deep Vein Thrombosis in a Mouse Model by Reducing the Expression of Pdpn

Current Medical Science 2024年第2期44卷 369-379页

作者： Ji LUO Jin zhou Jing-zeng LUO Hai-long WANG Xue-ling ZHAO ru-dan zhou Department of Intensive Care Unit The First People's Hospital of ZiyangZiyang 641300China Department of Orthopedics Kunming Medical University Second Affiliated HospitalKunming 650033China Department of Orthopedics Kunming Medical University First Affiliated HospitalKunming 650032China Department of Orthopedics The Third People's Hospital of Yunnan ProvinceKunming 650200China

Objective:Matrix metalloproteinase 13(MMP13)is an extracellular matrix protease that affects the progression of atherosclerotic plaques and arterial thrombi by degrading collagens,modifying protein structures and regulating inflammatory responses,but its role in deep vein thrombosis(DVT)has not been *** purpose of this study was to investigate the potential effects of MMP13 and MMP13-related genes on the formation of ***:We altered the expression level of MMP13 in vivo and conducted a transcriptome study to examine the expression and relationship between MMP13 and MMP13-related genes in a mouse model of *** screening genes possibly related to MMP13 in DVT mice,the expression levels of candidate genes in human umbilical vein endothelial cells(HUVECs)and the venous wall were *** effect of MMP13 on platelet aggregation in HUVECs was investigated in ***:Among the differentially expressed genes,interleukin 1 beta,podoplanin(Pdpn),and factor VIII von Willebrand factor(F8VWF)were selected for analysis in *** MMP13 was inhibited,the expression level of PDPN decreased significantly in *** HUVECs,overexpression of MMP13 led to an increase in the expression level of PDPN and induced platelet aggregation,while transfection of PDPN-siRNA weakened the ability of MMP13 to increase platelet ***:Inhibiting the expression of MMP13 could reduce the burden of DVT in *** mechanism involves downregulating the expression of Pdpn through MMP13,which could provide a novel gene target for DVT diagnosis and treatment.

关键词： deep vein thrombosis matrix metalloproteinase 13 podoplanin

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感潮河段单站等时距水位非线性优化预报模型

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水道港口 2017年第2期38卷 132-136,187页

作者：王如云李丹周钧汪天河海大学海洋学院南京210098 河海大学港口海岸与近海工程学院南京210098 河海大学水文水资源学院南京210098

目前感潮河段水位预报模型基于当前站水位、上游径流水位和下游海洋潮位数据进行预报,导致预见期受上游来流时间制约、上下游站数据缺失情况下无法进行预报、数据采集成本高等问题。文章假设感潮河段水位由径流因素和潮汐因素共同线性作... 详细信息

目前感潮河段水位预报模型基于当前站水位、上游径流水位和下游海洋潮位数据进行预报,导致预见期受上游来流时间制约、上下游站数据缺失情况下无法进行预报、数据采集成本高等问题。文章假设感潮河段水位由径流因素和潮汐因素共同线性作用,基于单站等时距水位数据,建立了包含一个径流动力修正系数和若干个潮汐调和分潮系数的非线性优化预报模型,并结合曲线拟合最小二乘法、潮汐调和分析法、梯度下降法,给出一个寻优的迭代算法,对模型参数进行优化辨识。模型应用于长江感潮河段部分观测站,水位预报精度较好,具有可行性和实用价值。

关键词：等时距感潮河段潮汐调和分析非线性优化预报模型

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Dynamic Multi-Graph Spatio-Temporal Graph Traffic Flow Prediction in Bangkok:An Application of a Continuous Convolutional Neural Network

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 579-607页

作者： Pongsakon Promsawat Weerapan Sae-dan Marisa Kaewsuwan Weerawat Sudsutad Aphirak Aphithana Department of Civil Engineering Faculty of EngineeringRamkhamkaeng UniversityBangkok10240Thailand Department of Computer Engineering Faculty of EngineeringRamkhamkaeng UniversityBangkok10240Thailand Department of Statistics Faculty of ScienceRamkhamkaeng UniversityBangkok10240Thailand

The ability to accurately predict urban traffic flows is crucial for optimising city ***,various methods for forecasting urban traffic have been developed,focusing on analysing historical data to understand complex mobility *** learning techniques,such as graph neural networks(GNNs),are popular for their ability to capture spatio-temporal ***,these models often become overly complex due to the large number of hyper-parameters *** this study,we introduce Dynamic Multi-Graph Spatial-Temporal Graph Neural Ordinary Differential Equation Networks(DMST-GNODE),a framework based on ordinary differential equations(ODEs)that autonomously discovers effective spatial-temporal graph neural network(STGNN)architectures for traffic prediction *** comparative analysis of DMST-GNODE and baseline models indicates that DMST-GNODE model demonstrates superior performance across multiple datasets,consistently achieving the lowest Root Mean Square Error(RMSE)and Mean Absolute Error(MAE)values,alongside the highest *** the BKK(Bangkok)dataset,it outperformed other models with an RMSE of 3.3165 and an accuracy of 0.9367 for a 20-min interval,maintaining this trend across 40 and 60 ***,on the PeMS08 dataset,DMST-GNODE achieved the best performance with an RMSE of 19.4863 and an accuracy of 0.9377 at 20 min,demonstrating its effectiveness over longer *** Los_Loop dataset results further emphasise this model’s advantage,with an RMSE of 3.3422 and an accuracy of 0.7643 at 20 min,consistently maintaining superiority across all time *** numerical highlights indicate that DMST-GNODE not only outperforms baseline models but also achieves higher accuracy and lower errors across different time intervals and datasets.

关键词： Graph neural networks convolutional neural network deep learning dynamic multi-graph spatio-temporal

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Thermal entanglement in a spin-1/2 Ising-Heisenberg butterfly-shaped chain with impurities

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Chinese Physics B 2020年第11期29卷 212-218页

作者： Meng-ru Ma Yi-dan Zheng Zhu Mao Bin zhou Department of Physics Hubei UniversityWuhan 430062China

We investigate the effect of impurities on the thermal entanglement in a spin-1/2 Ising-Heisenberg butterfly-shaped chain,where four interstitial Heisenberg spins are localized on the vertices of a rectangular plaquette in a unit *** using the transfer-matrix approach,we numerically calculate the partition function and the reduced density matrix of this *** bipartite thermal entanglement between different Heisenberg spin pairs is quantified by the *** also discuss the fluctuations caused by the impurities through the uniform distribution and the Gaussian *** the effects of the external magnetic field,temperature,Heisenberg and Ising interactions as well as the parameter of anisotropy on the thermal entanglement,our results show that comparing with the case of the clean model,in both the twoimpurity model and the impurity fluctuation model the entanglement is more robust within a certain range of anisotropic parameters and the region of the magnetic field where the entanglement occurred is also larger.

关键词： thermal entanglement Ising–Heisenberg butterfly-shaped chain impurities transfer-matrix approach

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Multi-Stream Temporally Enhanced Network for Video Salient Object Detection

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Computers, Materials & Continua 2024年第1期78卷 85-104页

作者： dan Xu Jiale ru Jinlong Shi School of Computer Science Jiangsu University of Science and TechnologyZhenjiang212100China

Video salient object detection(VSOD)aims at locating the most attractive objects in a video by exploring the spatial and temporal *** poses a challenging task in computer vision,as it involves processing complex spatial data that is also influenced by temporal *** the progress made in existing VSOD models,they still struggle in scenes of great background diversity within and between ***,they encounter difficulties related to accumulated noise and high time consumption during the extraction of temporal features over a long-term *** propose a multi-stream temporal enhanced network(MSTENet)to address these *** investigates saliency cues collaboration in the spatial domain with a multi-stream structure to deal with the great background diversity challenge.A straightforward,yet efficient approach for temporal feature extraction is developed to avoid the accumulative noises and reduce time *** distinction between MSTENet and other VSOD methods stems from its incorporation of both foreground supervision and background supervision,facilitating enhanced extraction of collaborative saliency *** notable differentiation is the innovative integration of spatial and temporal features,wherein the temporal module is integrated into the multi-stream structure,enabling comprehensive spatial-temporal interactions within an end-to-end *** experimental results demonstrate that the proposed method achieves state-of-the-art performance on five benchmark datasets while maintaining a real-time speed of 27 fps(Titan XP).Our code and models are available at https://***/ruJiaLe/MSTENet.

关键词： Video salient object detection deep learning temporally enhanced foreground-background collaboration

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Influence of Fe on Microstructure and Mechanical Properties in Pdoped Ni–Cr–Fe Alloys

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Acta Metallurgica Sinica(English Letters) 2019年第6期32卷 771-779页

作者： Xin-Tong Lian Wen-ru Sun Xin Xin Fang Liu dan-dan Zheng Institute of Metal Research Chinese Academy of SciencesShenyang 110016China School of Materials Science and Engineering Shanghai UniversityShanghai 200444China

The influence of Fe on the microstructure and mechanical properties of P-doped Ni–Cr–Fe alloys has been *** showed that increasing Fe content refined the dendrite microstructure and enhanced the solubility of P in as-cast *** change of microhardness in different dendrite regions was attributed to the segregation of P atoms in solid solution state,which had strengthening *** Fe contents from 15.2 to 60.7 wt%reduced the yield strength and tensile strength but had little influence on the elongation of *** stress rupture life of alloys after heat treatment decreased with the increment of Fe contents,and the failure fracture modes transferred from transgranular to intergranular fracture *** change of fracture modes was due to the weakness of grain boundaries caused by the increment of *** addition,the precipitation of M23C6 was believed to be related to the segregation of P toward grain boundaries,which led to the fluctuation of carbon and chromium atoms near the grain boundaries in alloys with low Fe ***,the increment of Fe decreased the strength of matrix and changed the existence of P atoms and the precipitates at grain boundaries.

关键词： Fe P Segregation Precipitate Mechanical properties

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Effects of Phosphorus and Iron on Microstructures and Mechanical Properties in NiCrFe-Based Alloys

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Acta Metallurgica Sinica(English Letters) 2019年第5期32卷 659-667页

作者： Xin-Tong Lian Wen-ru Sun Fang Liu dan-dan Zheng Xin Xin Institute of Metal Research Chinese Academy of Sciences School of Materials Science and Engineering University of Science and Technology of China

The microstructures and mechanical properties, especially creep properties, of the NiCrFe-based alloys with various contents of phosphorus and iron were investigated. The results showed that the tensile yield strength decreased with increasing iron contents while had no obvious change with the addition of phosphorus. For creep properties, the alloy with15.8 wt% iron and 0.09 wt% phosphorus possessed the longest creep life(679 h) among all alloys. Only M_(23)C_6 was formed in the alloys with low phosphorus contents, while both intergranular M_3P and M_(23)C_6 precipitated with the increment of phosphorus, which enhanced the strength of grain boundary by hindering the movements of dislocations during creep tests. The reasons for the enhancement of creep life were mainly related to the solid solution strengthening effect of phosphorus and optimization of grain boundary precipitations by phosphorus.

关键词： NiCrFe-based alloys Phosphorus Iron Microstructures Creep properties

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Design a Hybrid Energy-Supply for the Electrically Driven Heavy-Duty Hexapod Vehicle

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Journal of Bionic Engineering 2023年第4期20卷 1434-1448页

作者： Zhenyu Xu Haoyuan Yi dan Liu ru Zhang Xin Luo State Key Laboratory of Digital Manufacturing Equipment and Technology Huazhong University of Science and TechnologyWuhan430074China Research Institute Inner Mongolia First Machinery Group Co.LtdBaotou014030China

Increasing the power density and overload capability of the energy-supply units(ESUs)is always one of the most challenging tasks in developing and deploying legged vehicles,especially for heavy-duty legged vehicles,in which significant power fluctuations in energy supply exist with peak power several times surpassing the average *** ESUs with high power density and high overload can compactly ensure fluctuating power source supply on *** can avoid the ultra-high configuration issue,which usually exists in the conventional lithium-ion battery-based or engine-generator-based ***,it dramatically reduces weight and significantly increases the loading and endurance capabilities of the legged *** this paper,we present a hybrid energy-supply unit for a heavy-duty legged vehicle combining the discharge characteristics of lithium-ion batteries and peak energy release/absorption characteristics of supercapacitors to adapt the ESU to high overload power *** parameters of the lithium-ion battery pack and supercapacitor pack inside the ESU are optimally matched using the genetic algorithm based on the energy consumption model of the heavy-duty legged *** experiment results exhibit that the legged vehicle with a weight of 4.2 tons can walk at the speed of 5 km/h in a tripod gait under a reduction of 35.39%in weight of the ESU compared to the conventional lithium-ion battery-based solution.

关键词： Heavy-duty legged vehicles Hybrid energy-supply unit Power fluctuation Optimal matching of lithium-ion battery pack and supercapacitor pack

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Application of machine learning to the Vs-based soil liquefaction potential assessment

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Journal of Mountain Science 2023年第8期20卷 2197-2213页

作者： SUI Qi-ru CHEN Qin-huang WANG dan-dan TAO Zhi-gang State Key Laboratory for GeoMechanics and Deep Underground Engineering China University of Mining and Technology(Beijing)Beijing 100083China School of Mechanics and Civil Engineering China University of Mining and Technology(Beijing)Beijing 100083China

Earthquakes can cause violent liquefaction of the soil, resulting in unstable foundations that can cause serious damage to facilities such as buildings, roads, and dikes. This is a primary cause of major earthquake disasters. Therefore, the discrimination and prediction of earthquake-induced soil liquefaction has been a hot issue in geohazard research. The soil liquefaction assessment is an integral part of engineering practice. This paper evaluated a dataset of 435 seismic sand liquefaction events using machine learning algorithms. The dataset was analyzed using seven potential assessment parameters. Ten machine learning algorithms are evaluated for their ability to assess seismic sand liquefaction potential, including Linear Discriminant Analysis(LDA), Quadratic Discriminant Analysis(QDA), Naive Bayes(NB), KNearest Neighbor(KNN), Artificial Neural Network(ANN), Classification Tree(CT), Support Vector Machine(SVM), Random Forest(RF), e Xtreme Gradient Boosting(XGBoost), Light Gradient Boosting Machine(Light GBM). A 10-fold cross-validation(CV) method was used in the modeling process to verify the predictive performance of the machine learning models. The final percentages of significant parameters that influenced the prediction results were obtained as Cyclic Stress Ratio(CSR) and Shear-Wave Velocity( VS1) with 56% and 38%, respectively. The final machine learning algorithms identified as suitable for seismic sand liquefaction assessment were the CT, RF, XGBoost algorithms, with the RF algorithm performing best.

关键词： Seismic soil liquefaction Machine learning Assessment Liquefaction potential shear wave velocity

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Identification of the resistance gene to powdery mildew in Chinese wheat landrace Baiyouyantiao

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Journal of Integrative Agriculture 2018年第1期17卷 37-45页

作者： XU Xiao-dan FENG Jing FAN Jie-ru LIU Zhi-yong LI Qiang zhou Yi-lin MA Zhan-hong State Key Laboratory for Biology of Plant Diseases and Insect Pests/Institute of Plant Protection Chinese Academy of Agricultural Sciences College of Plant Protection China Agricultural University State Key Laboratory of Plant Cell and Chromosome Engineering/Institute of Genetics and Developmental Biology Chinese Academy of Sciences College of Plant Protection Northwest A&F University/State Key Laboratory of Crop Stress Biology for Arid Areas

Powdery mildew, caused by Blumeria graminis f. sp. tritici （Bgt）, is one of the most damaging diseases to wheat in the world. The cultivation of resistant varieties of wheat is essential for controlling the powdery mildew epidemic. Wheat landraces are important resources of resistance to many diseases. Mapping powdery mildew resistance genes from wheat landraces will promote the development of new varieties with disease resistance. The Chinese wheat landrace Baiyouyantiao possesses characteristic of disease resistance to powdery mildew. To identify the resistance gene in this landrace, Baiyouyantiao was crossed with the susceptible cultivar Jingshuang 16 and seedlings of parents and F1, BC1, F2, and F~：3 were tested with Bgt isolate E09. The genetic results showed that the resistance of Baiyouyantiao to E09 was controlled by a single recessive gene, tentatively designated PmBYYT. An Illumina wheat 90K single-nucleotide polymorphism （SNP） array was applied to screen polymorphisms between F2-resistant and F2-susceptible DNA bulks for identifying the chromosomal location of PmBYYT. A high percentage of polymorphic SNPs between the resistant and susceptible DNA bulks was found on chro- mosome 7B, indicating that PmBYYT may be located on this chromosome. A genetic linkage map of PmBYYTconsisting of two simple sequence repeat markers and eight SNP markers was developed. The two flanking markers were SNP markers W7BL-8 and W7BL-15, with genetic distances of 3 and 2.9 cM, respectively. The results of this study demonstrated the rapid characterization of a wheat disease resistance gene and SNP marker development using the 90K SNP assay. The flanking markers of gene PmBYYTwill benefit marker-assisted selection （MAS） and map-based cloning in breeding wheat cultivars with powdery mildew resistance.

关键词： wheat landrace powdery mildew genetic mapping single-nucleotide polymorphism (SNP) array

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