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Translate Plant Metabolism into Modern Agriculture： A Starting Point

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Molecular Plant 2012年第2期5卷 291-293页

作者： Xiao-Ya Chen Lai-Geng Li ji-rong huang Yong-Ling Ruan Xue-Min Wang Li Li unknown

Plants, the primary producers on the Earth, use solar energy to convert CO2 and H2O into various organic compounds. Over the past 10 000 years, humans have exploited the plant synthesizing capability and developed agricultural practice to meet the basic needs for food, fiber, energy, chemicals, and medicines. Actually, all of the products are an assortment of compounds synthesized in plants though a variety of metabolic processes. It has been estimated that any given plant species can synthesize 5000-25 000 different compounds （Trethewey, 2004）. More than 100 000 metabolites, which may account for approximately 10% of the total natural products, have been identified in the plant kingdom.

关键词： Translate Plant Metabolism

Microstructure and Internal Friction Behavior of Laser 3D Printed Fe-Based Amorphous Composites

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Acta Metallurgica Sinica(English Letters) 2024年第1期37卷 196-204页

作者： Shuilong huang Qingjun Chen Li ji Kan Wang Guosheng huang School of Material Science and Engineering Nanchang Hangkong UniversityNanchang330063China State Key Laboratory for Marine Corrosion and Protection Luoyang Ship Material Research Institute(LSMRI)Qingdao266237China

Laser 3D printing,also known as laser additive manufacturing(LAM),is favored for its ability to form bulk metallic glass(BMG)and its composite materials(BMGcs)with freeform *** this work,two different kinds of Fe_(41)Co_(7)Cr_(15)Mo_(14)C_(15)B_(6)Y_(2)amorphous coatings(A and B)were prepared by using LAM technology under air-and water-cooled conditions,respectively;meanwhile,to reduce the cracks generated due to the residual thermal stresses,coating C obtained by air-sweep annealing of B with a low energy-density *** morphology and amorphous content and microstructure of the coatings were investigated,the results show many cracks in coating B deposited under water-cooled conditions,and its microstructure shows an amorphous-crystal-nanocrystalline mixed *** was suppressed in coating C,obtained by air-sweep annealing based on coating B,but the amorphous content was reduced from 32.6 to 13.4%.And the hardness and corrosion resistance of the coating will increase with the increase in the amorphous ***,the internal friction behavior of a BMGcs was prepared on the basis of the process of sample C is compared with that of as-cast amorphous *** results show that the low temperature internal friction behavior of BMGcs is affected by the defects produced during printing,and the high temperature internal friction behavior is affected by the precipitated hard phase.

关键词： Laser 3D printing Amorphous coating Microstructure Corrosion resistance Internal friction behavior

Machine learning with active pharmaceutical ingredient/polymer interaction mechanism:Prediction for complex phase behaviors of pharmaceuticals and formulations

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Chinese Journal of Chemical Engineering 2024年第2期66卷 263-272页

作者： Kai Ge Yiping huang Yuanhui ji jiangsu Province Hi-Tech Key Laboratory for Biomedical Research School of Chemistry and Chemical EngineeringSoutheast UniversityNanjing 211189China

The high throughput prediction of the thermodynamic phase behavior of active pharmaceutical ingredients(APIs)with pharmaceutically relevant excipients remains a major scientific challenge in the screening of pharmaceutical *** this work,a developed machine-learning model efficiently predicts the solubility of APIs in polymers by learning the phase equilibrium principle and using a few molecular *** the few-shot learning framework,thermodynamic theory(perturbed-chain statistical associating fluid theory)was used for data augmentation,and computational chemistry was applied for molecular descriptors'*** results showed that the developed machine-learning model can predict the API-polymer phase diagram accurately,broaden the solubility data of APIs in polymers,and reproduce the relationship between API solubility and the interaction mechanisms between API and polymer successfully,which provided efficient guidance for the development of pharmaceutical formulations.

关键词： Multi-task machine learning Density functional theory Hydrogen bond interaction Miscibility Solubility

In-situ powder mixing for laser-based directed energy deposition of functionally graded materials

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Advances in Manufacturing 2024年第1期12卷 150-166页

作者： ji-Peng Chen Shou-Chun Xie He huang School of Mechanical and Electronic Engineering Nanjing Forestry UniversityNanjing210037People’s Republic of China Nanjing Huirui Photoelectric Technology Co. LtdNanjing211121People’s Republic of China

The mixing of powders is a highly relevant field under additive manufacturing,however,it has attracted limited interest to *** in-situ mixing of various powders remains a significant *** paper proposes a new method utilizing a static mixer for the in-situ mixing of multiple powders through the laser-based directed energy deposition(DED)of functionally graded ***,a powder-mixing experimental platform was established;WC and 316L powders were selected for the mixing ***,scanning electron microscopy,energy dispersive spectroscopy,and image processing were used to visually evaluate the homogeneity and proportion of the in-situ mixed ***,powder-mixing simulations were conducted to determine the powder-mixing *** the simulations,a powder carrier gas flow field and particle mixing were ***,a WC/316L metal matrix composite sample was produced using laser-based DED to verify the application potential of the static *** was found that the static mixer could adjust the powder ratio online,and a response time of 1–2 s should be considered when adjusting the ratio of the mixed powder.A feasible approach for in-situ powder mixing for laser-based DED was demonstrated and investigated,creating the basis for functionally graded materials.

关键词： Laser Deposition Static mixer Powder mixing Functionally graded materials

Enhancing Low-Frequency Microwave Absorption Through Structural Polarization Modulation of MXenes

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Nano-Micro Letters 2024年第10期16卷 435-452页

作者： Bo Shan Yang Wang Xinyi ji Yi huang College of Light Industry Science and Engineering State Key Laboratory of Biobased Fiber Manufacturing TechnologyTianjin University of Science and TechnologyTianjin 300457People's Republic of China National Institute for Advanced Materials Tianjin Key Laboratory of Metal and Molecule Based Material ChemistryKey Laboratory of Functional Polymer MaterialsCollaborative Innovation Center of Chemical Science and Engineering(Tianjin)School of Materials Science and EngineeringNankai UniversityTianjin 300350People's Republic of China

Two-dimensional carbon-based materials have shown promising electromagnetic wave absorption capabilities in mid-and high-frequency ranges,but face challenges in low-frequency absorption due to limited control over polarization response mecha-nisms and ambiguous resonance *** this study,we pro-pose a novel approach to enhance absorption efficiency in aligned three-dimensional(3D)MXene/CNF(cellulose nanofibers)cavities by modifying polarization properties and manipulating resonance response in the 3D MXene *** controlled polarization mechanism results in a significant shift of the main absorption region from the X-band to the S-band,leading to a remarkable reflection loss value of-47.9 dB in the low-frequency ***,our findings revealed the importance of the oriented electromagnetic coupling in influencing electromagnetic response and microwave absorption *** present study inspired us to develop a generic strategy for low-frequency tuned absorption in the absence of magnetic element participation,while orientation-induced polarization and the derived magnetic resonance coupling are the key controlling factors of the method.

关键词： Hierarchical structure MXene Microwave absorption Low-frequency

Machine learning-assisted sparse observation assimilation for real-time aerodynamic field perception

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Science China(Technological Sciences) 2024年第5期67卷 1458-1469页

作者： ZHAO QingYu huang Jun GUO YuXin PAN YuXuan ji jingjing huang YongAn State Key Laboratory of Intelligent Manufacturing Equipment and Technology School of Mechanical Science and EngineeringHuazhong University of Science and TechnologyWuhan 430074China

Accurate aerodynamic distribution perception and real-time flight state evaluation are crucial for flight safety,e.g.,stall ***,the observations are usually sparse due to limitations in sensor mounting space and cost,and a reconstruction technology is urgently ***,a machine learning-assisted assimilation method based on sparse observations has been *** from the traditional reconstruction methods focusing on boundary condition correction,the proposed method formulates the flow field pressure distribution as a linear superposition of flow field modes,thereby forming a real-time reconstruction pattern that combines offline modal extraction using computational fluid dynamics(CFD)with real-time determination of modal weights using a neural *** this study,CFD simulations were conducted under 800different operating conditions for common modal extraction and model *** weights of these modes were determined online based on merely five observations for reconstructing the full pressure field.A pressure reconstruction with a relative error of 6.1%and a mean square error of 0.003 was achieved within the prescribed condition *** computational cost was just2 ms for each reconstruction run,significantly faster than the 20 min required by the classical reconstruction ensemble transform Kalman *** also showed that the method maintains almost the same accuracy amidst 1.5%measurement *** practical examples,shock waves and the change of lift coefficient were analyzed using the proposed method,providing remarkable evidence for the capability of the method in supporting stall *** validate the method’s effectiveness and explore its potential in real-time and accurate monitoring of an aircraft.

关键词： aerodynamic force sparse observation neural networks pressure field reconstruction

Effect of Tanshinone IIA on High Glucose-induced Apoptosis and Oxidative Stress Damage in Vascular Endothelial Cells

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Chinese Journal of Biomedical Engineering 2024年第2期33卷 62-68页

作者： QIU Shui-lin huang rong huang jian-qing QIU rong-shui Longyan First Affiliated Hospital of Fujian Medical University Xiamen Medical College Affiliated Haicang Hospital

Objective: The primary cause of microvascular disease in diabetic complications is long-term hyperglycemia, wherein the damage and apoptosis of vascular endothelial cells play a significant role. Sodium tanshinone IIA sulfonate(STS) has been found to have beneficial effects on cardiovascular health. This study aimed to investigate the impact of STS on high glucose-induced apoptosis and oxidative stress damage in vascular endothelial cells, as well as its potential protective mechanisms. Methods:Human umbilical vein endothelial cells(HUVECs) were divided into five groups:low-glucose group, high-glucose group, and three STS groups(STS-a, STS-b, and STS-c). The low-glucose group was incubated with DMEM low-sugar medium containing 5.5 mmol·L-1glucose, while the high-glucose group was treated with 33.3mmol·L-1glucose. The STS groups were exposed to 10, 30, and 50 μg·m L-1of STS,respectively. Each group was cultured for 72 h, and the MTT method was utilized to assess cell proliferation. Additionally, flow cytometry was employed to monitor changes in cell apoptosis and cellular oxidative stress indicators at 24, 48, and 72 h of cell culture in each group. Results: As time went on, the cell proliferation ability and apoptosis rate of each group gradually increased. The high-glucose group exhibited lower proliferation ability compared to the other groups. The STS-c group demonstrated the highest OD value for proliferation ability(24 h: 1.19±0.12; 48 h: 1.20±0.13; 72 h:1.25 ±0.12), but it was still lower than that of the low-sugar group. Notably, the high-glucose group had the highest cell apoptosis rate, while the low-glucose group had the lowest. The apoptosis rate of the STS-c group(24 h: 8.02±0.13; 48 h: 10.10±0.12;72 h: 13.18 ±0.11)% was between that of the low-glucose group and the high-glucose group, and lower than the STS-a and STS-b groups. Furthermore, the high-glucose group exhibited the highest malondialdehyde and nitric oxide synthase activities, as well as super

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Predicting the International Roughness Index of JPCP and CRCP Rigid Pavement:A Random Forest(RF)Model Hybridized with Modified Beetle Antennae Search(MBAS)for Higher Accuracy

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Computer Modeling in Engineering & Sciences 2024年第5期139卷 1557-1582页

作者： Zhou ji Mengmeng Zhou Qiang Wang jiandong huang College of Civil and Environmental Engineering Hunan University of Science and EngineeringYongzhou425006China School of Mines China University of Mining and TechnologyXuzhou221116China School of Civil Engineering Guangzhou UniversityGuangzhou510006China

To improve the prediction accuracy of the International Roughness Index(IRI)of Jointed PlainConcrete Pavements(JPCP)and Continuously Reinforced Concrete Pavements(CRCP),a machine learning approach is developed in this study for the modelling,combining an improved Beetle Antennae Search(MBAS)algorithm and Random Forest(RF)*** 10-fold cross-validation was applied to verify the reliability and accuracy of the model proposed in this *** importance scores of all input variables on the IRI of JPCP and CRCP were analysed as *** results by the comparative analysis showed the prediction accuracy of the IRI of the newly developed MBAS and RF hybrid machine learning model(RF-MBAS)in this study is higher,indicated by the RMSE and R values of 0.2732 and 0.9476 for the JPCP as well as the RMSE and R values of 0.1863 and 0.9182 for the *** accuracy of this obtained result far exceeds that of the IRI prediction model used in the traditional Mechanistic-Empirical Pavement Design Guide(MEPDG),indicating the great potential of this developed *** importance analysis showed that the IRI of JPCP and CRCP was proportional to the corresponding input variables in this study,including the total joint faulting cumulated per KM(TFAULT),percent subgrade material passing the 0.075-mm Sieve(P_(200))and pavement surface area with flexible and rigid patching(all Severities)(PATCH)which scored higher.

关键词： Cement pavement JPCP CRCP RF-MBAS IRI

WeldNet:A voxel-based deep learning network for point cloud annular weld seam detection

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Science China(Technological Sciences) 2024年第4期67卷 1215-1225页

作者： WANG Hui rong YouMin XU jiaJun XIANG SongMing PENG YiFan huang Yu State Key Laboratory of Intelligent Manufacturing Equipment and Technology Huazhong University of Science and TechnologyWuhan 430074China School of Mechanical Science and Engineering Huazhong University of Science and TechnologyWuhan 430074China

Weld seam detection is an important part of automated *** present,few studies have been conducted on annular weld seams,and a lot of defects exist in the point cloud model of the tube sheet obtained by RGB-D cameras and photography *** at the above problems,this paper proposed an annular weld seam detection network named WeldNet where a voxel feature encoding layer was adaptively improved for annular weld seams,the sparse convolutional network and region proposal network(RPN)were used to detect annular weld seam position,and an annular weld seam detection loss function was ***,an annular weld seam dataset was established to train the *** with the random sampling consistency(RANSAC)method,WeldNet has a higher detection accuracy,as well as a higher detection success rate which has increased by 23%.Compared with U-Net,WeldNet has been proven to achieve a better detection result,and the intersection over the union of the weld seam detection is improved by 17.8%.

关键词： deep learning point cloud weld seam detection welding annular weld seam