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Artificial Intelligence in Agriculture 2023年第3期9卷 110-126页

作者： Yuanzhi Pan Yuzhen Zhang Xiaoping Wang xiang Xiang Gao Zhongyu Hou Artificial Intelligence Lab Zhenjiang Hongxiang Automation Technology Co.Ltd.Zhenjiang 212050Jiangsu ProvinceChina School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University800 Dongchuan RoadShanghai 200030China School of Innovation and Entrepreneurship Jiangsu University301 Xuefu RoadZhenjiang 212013Jiangsu ProvinceChina Shanghai Picowave Technology Co.Ltd. Shanghai 201802China Guangzhou Institute of Advanced Technology Chinese Academy of Science(GIAT)Guangzhou 511458China

Modern pig farming leaves much to be desired in terms of efficiency,as these systems rely mainly on electromechanical controls and can only categorize pigs according to their weight.This method is not only inefficient but also escalates labor expenses and heightens the threat of zoonotic diseases.Furthermore,confining pigs in large groups can exacerbate the spread of infections and complicate the monitoring and care of ill pigs.This research executed an experiment to construct a deep-learning sorting mechanism,leveraging a dataset infused with pivotal metrics and breeding imagery gathered over 24 months.This research integrated a Kalman filterbased algorithm to augment the precision of the dynamic sorting operation.This research experiment unveiled a pioneering machine vision sorting system powered by deep learning,adept at handling live imagery for multifaceted recognition objectives.The Individual recognition model based on Residual Neural Network(ResNet)monitors livestock weight for sustained data forecasting,whereas the Wasserstein Generative Adversarial Nets(WGAN)image enhancement algorithm bolsters recognition in distinct settings,fortifying the model's resilience.Notably,system can pinpoint livestock exhibiting signs of potential illness via irregular body appearances and isolate them for safety.Experimental outcomes validate the superiority of this proposed system over traditional counterparts.It not only minimizes manual interventions and data upkeep expenses but also heightens the accuracy of livestock identification and optimizes data usage.This findings reflect an 89%success rate in livestock ID recognition,a 32%surge in obscured image recognition,a 95%leap in livestock categorization accuracy,and a remarkable 98%success rate in discerning images of unwell pigs.In essence,this research augments identification efficiency,curtails operational expenses,and provides enhanced tools for disease monitoring.

关键词： Pig monitoring Image recognition Sorting system WGAN ResNet

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Recent progress on pure organic room temperature phosphorescent polymers

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Aggregate 2021年第4期2卷 87-99页

作者： Hao gao xiang Ma Key Laboratory for Advanced Materials and Feringa Nobel Prize Scientist Joint Research Center Frontiers Science Center for Materiobiology and Dynamic ChemistrySchool of Chemistry and Molecular EngineeringEast China University of Science&TechnologyShanghaiChina

So far,pure organic room temperature phosphorescence(RTP)materials are developing rapidly and have become a research hotspot in the scientific community.They are regarded as valuable resources with great potential for development in many fields,such as biomedicine,information multi-level encryption,smart anticounterfeiting,and so on.Among them,a series of pure organic RTP polymer systems emerged at the right moment based on the excellent properties of polymers such as easy processing,low cost,and good biocompatibility.Furthermore,the huge molecular weight,long-chain intertwined structure,and potential interactions with phosphors of polymers make them a focus for RTP emission.Herein,we describe the development history of this system in detail,explore the necessary factors for highly efficient emission from the phosphorescence emission process,and based on the dual effects of enhancing phosphorescence emission and shortening luminescence lifetime brought by heavy atoms,we summarize the internal mechanism and achievements of various researches from the perspective of heavy atom–containing and non-heavy atom systems.

关键词： heavy atom effect room temperature phosphorescence polymer

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An equine disease diagnosis expert system based on improved reasoning of evidence credibility

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Information Processing in Agriculture 2019年第3期6卷 414-423页

作者： Hongyan gao Guimiao Jiang Xiang Gao Jianhua Xiao Hongbin Wang Department of Veterinary Surgery Northeast Agricultural UniversityHarbin 150030China National Engineering Research Center for Gelatin-based Traditional Chinese Medicine Dong-E-E-Jiao Co.Ltd.Liaocheng 252201China

In China,there is a troubling shortage of well-trained equine veterinarians,leaving the needs of many equine farmers unmet.This is especially true with respect to the diagnosis of equine diseases.To solve this shortcoming,an equine disease diagnosis expert system was developed.For the aspect of knowledge representation,the structure of equine disease diagnosis knowledge was analyzed using an ontology system.Next,the clinical signs were described using an object-attribute-value(O-A-V)format,and the knowledge representation was then expressed using production rules.With respect to the reasoning mechanism,the weights of the clinical signs and promoted confidence factors(PCF)were combined to express information and rules pertaining to clinical signs with an associated level of uncertainty.The model was established based on improved reasoning of evidence credibility.Finally,using the *** platform and the SQL Server 2008 database,the equine disease diagnosis expert system based on the B/S structure has been developed,and is capable of reliably diagnosing 40 of the most common equine diseases.A functional evaluation of the system was conducted,and the diagnostic accuracy was observed to be 88%.This study demonstrates a bright prospect for the popularization and application of the system through continuous system maintenance and knowledge-based updates.

关键词： Equine disease Diagnosis Expert system Object-based ontology Evidence credibility

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Transfer-free chemical vapor deposition graphene for nitride epitaxy: challenges, current status and future outlook

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Science China Chemistry 2024年第3期67卷 824-840页

作者： Xiang Gao Senlin Li Jingfeng Bi Kaixuan Zhou Meng Li Zhongfan Liu Jingyu Sun College of Energy Soochow Institute for Energy and Materials InnovationsSUDA-BGI Collaborative Innovation CenterKey Laboratory of Advanced Carbon Materials and Wearable Energy Technologies of Jiangsu ProvinceSoochow UniversitySuzhou 215006China Beijing Graphene Institute Beijing 100095China Xiamen Silan Advanced Compound Semiconductor Co.Ltd. Xiamen 361026China

Graphene, a two-dimensional material with outstanding electrical and mechanical properties, has attracted considerable attention in the field of semiconductor technologies due to its potential use as a buffer layer for the epitaxial Ⅲ-nitride growth. In recent years, significant progress has been made in the chemical vapor deposition growth of graphene on various insulating substrates for the nitride epitaxy, which offers a facile, inexpensive, and easily scalable methodology. However, certain challenges are still present in the form of producing high-quality graphene and achieving optimal interface compatibility with Ⅲ-nitride materials.In this review, we provide an overview of the bottlenecks associated with the transferred graphene fabrication techniques and the state-of-the-art techniques for the transfer-free graphene growth. The present contribution highlights the current progress in the transfer-free graphene growth on different insulating substrates, including sapphire, quartz, SiO_(2)/Si, and discusses the potential applications of transfer-free graphene in the Ⅲ-nitride epitaxy. Finally, it includes the prospects of the transfer-free graphene growth for the Ⅲ-nitride epitaxy and the challenges that should be overcome to realize its full potential in this field.

关键词： Transfer-free chemical vapor deposition graphene for nitride epitaxy challenges current status and future outlook graphene

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Optimized LDPC differential-encoded 16QAM scheme for high-speed transmission systems

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Journal of Systems Engineering and Electronics 2014年第5期25卷 728-734页

作者： Zhanji Wu Xiang Gao Zhiyu Xiao School of Information and Communication Engineering Beijing University of Posts and Telecommunications Huawei Technology Limited Corporation

The 16-ary quadrature amplitude modulation （16QAM） is a high spectral efficient scheme for high-speed transmission systems. To remove the phase ambiguity in the coherent detection system, differential-encoded 16QAM （DE-16QAM） is usually used, however, it will cause performance degradation about 3 dB as compared to the conventional 16QAM. To overcome the performance loss, a serial concatenated system with outer low density parity check （LDPC） codes and inner DE-16QAM is proposed. At the receiver, joint iterative differential demodulation and decoding （ID） is carried out to approach the maximum likelihood performance. Moreover, a genetic evolution algorithm based on the extrinsic information transfer chart is proposed to optimize the degree distribution of the outer LDPC codes. Both theoretical analyses and simulation results indicate that this algorithm not only compensates the performance loss, but also obtains a significant performance gain, which is up to 1 dB as compared to the conventional non-DE-16QAM.

关键词： quadrature amplitude modulation （QAM） low density parity check （LDPC） code genetic evolution （GE） algorithm iterative demodulation and decoding （ID） extrinsic information transfer （EXIT） chart.

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Scalable and controllable synthesis of 2D high-proportion 1T-phase MoS_(2)

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Nano Research 2020年第11期13卷 2933-2938页

作者： Xiang Gao Liukang Xiong Jiabin Wu Jun Wan Liang Huang Wuhan National Laboratory for Optoelectronics Huazhong University of Science and TechnologyWuhan430074China State Key Laboratory of Materials Processing and Die&Mold Technology School of Materials Science and EngineeringHuazhong University of Science and TechnologyWuhan430074China

Two-dimensional molybdenum disulfide(2D MoS_(2))is considered as a promising candidate for many applications due to its unique structure and properties.However,the controllable synthesis of large-scale and high-quality 2D 1T-phase MoS_(2)is still a challenge.Herein,we present the scalable and controllable synthesis of 2D MoS2 from 2H to 1T@2H phase by using K_(2)SO_(4)salt as a simultaneous high-temperature sulfur source and template.The as-synthesized 1T@2H-2D MoS_(2)exhibits a high yield and can be easily assembled into freestanding electrode with high specific capacitance of 434 F/g at a scan rate of 1 mV/s in LiClO_(4)ethylene carbonate/dimethyl carbonate(EC/DMC).Moreover,various single-crystal 2D transition metal sulfides(WS_(2),PbS,MnS and Ni_(9)S_(8))and 2D S-doped carbon can be synthesized using this method.We believe that this study may provide a new sight for scalable and controllable synthesis of other 2D materials beyond 2D MoS_(2).

关键词： two-dimensional material MoS_(2) 1T phase scalable synthesis controllable synthesis

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Post-acute ischemic stroke hyperglycemia aggravates destruction of the blood-brain barrier

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Neural Regeneration Research 2024年第6期19卷 1344-1350页

作者： Tianqi Xu Jianhong Yang Yao Xu Xiaofeng Wang Xiang Gao Jie Sun Chenhui Zhou Yi Huang Department of Neurology The First Affiliated Hospital of Ningbo University Department of General Surgery The First Affiliated Hospital of Ningbo University Department of Neurosurgery The First Affiliated Hospital of Ningbo University Key Laboratory of Precision Medicine for Atherosclerotic Diseases of Zhejiang Province

Post-acute ischemic stroke hyperglycemia increases the risk of hemorrhagic transformation, which is associated with blood-brain barrier disruption. Brain microvascular endothelial cells are a major component of the blood-brain barrier. Intercellular mitochondrial transfer has emerged as a novel paradigm for repairing cells with mitochondrial dysfunction. In this study, we first investigated whether mitochondrial transfer exists between brain microvascular endothelial cells, and then investigated the effects of post-acute ischemic stroke hyperglycemia on mitochondrial transfer between brain microvascular endothelial cells. We found that healthy brain microvascular endothelial cells can transfer intact mitochondria to oxygen glucose deprivation-injured brain microvascular endothelial cells. However, post-oxygen glucose deprivation hyperglycemia hindered mitochondrial transfer and exacerbated mitochondrial dysfunction. We established an in vitro brain microvascular endothelial cell model of the blood-brain barrier. We found that post-acute ischemic stroke hyperglycemia reduced the overall energy metabolism levels of brain microvascular endothelial cells and increased permeability of the blood-brain barrier. In a clinical study, we retrospectively analyzed the relationship between post-acute ischemic stroke hyperglycemia and the severity of hemorrhagic transformation. We found that post-acute ischemic stroke hyperglycemia serves as an independent predictor of severe hemorrhagic transformation. These findings suggest that post-acute ischemic stroke hyperglycemia can aggravate disruption of the blood-brain barrier by inhibiting mitochondrial transfer.

关键词： acute ischemic stroke blood-brain barrier brain microvascular endothelial cells mitochondrial transfer stress hyperglycemia

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Thick exchange layer evaporation model with natural convection effect and evaporation experimental study for multicomponent droplet

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Chinese Journal of Aeronautics 2020年第7期33卷 1903-1918页

作者： Fang WANG Xiang Gao Yangchun XIAO Zhaoyang WU Jie JIN Aero-Engine Numerical Simulation Research Center School of Energy and Power EngineeringBeihang UniversityBeijing 100083China

In order to investigate the high-temperature evaporation characteristics of multicomponent liquid fuel,three kinds of blended fuel:n-heptane/n-decane/RP-3 aviation kerosene-ethanol were experimentally studied with and without forced convection.Further,based on zerodiffusion and infinite diffusion concept,this study expanded Thick Exchange Layer evaporation model with Natural Convection effect(NC-TEL)to multicomponent liquid fuels.The experimental results show that the droplet evaporation rate increases significantly with the increase of ambient temperature.Higher temperature leads to more significant relationships between the composition ratio and the evaporation rate.The effect of forced convection is not obviously under the circumstance in this paper.Then,the evaporation models were validated by experimental data.In general,the new NC-TEL model behaves better than the Ranz-Marshall(R-M)model,and the prediction accuracy at high temperature is improved by 8%to 35%.In lower temperature conditions,the prediction of zero-diffusion NC-TEL model is better than the infinite diffusion NC-TEL model.In high-temperature conditions,for n-heptane-ethanol droplet,the predictions of NC-TEL model are accurate,but for n-decane/RP-3 aviation kerosene-ethanol,the predictions are lower than experimental results.This may be caused by the micro-explosion phenomenon and the Marangoni phenomenon.

关键词： Droplet Evaporation rate Multicomponent fuel evaporation model Natural convection Suspended droplet experiment Thick exchange layer model

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FlowDNN:a physics-informed deep neural network for fast and accurate flow prediction

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Frontiers of Information Technology & Electronic Engineering 2022年第2期23卷 207-219页

作者： Donglin CHEN Xiang Gao Chuanfu XU Siqi WANG Shizhao CHEN Jianbin FANG Zheng WANG College of Computer National University of Defense TechnologyChangsha 410073China State Key Laboratory of High Performance Computing National University of Defense TechnologyChangsha 410073China School of Computing University of LeedsLeeds LS29JTUK

For flow-related design optimization problems,e.g.,aircraft and automobile aerodynamic design,computational fluid dynamics(CFD)simulations are commonly used to predict flow fields and analyze performance.While important,CFD simulations are a resource-demanding and time-consuming iterative process.The expensive simulation overhead limits the opportunities for large design space exploration and prevents interactive design.In this paper,we propose Flow DNN,a novel deep neural network(DNN)to efficiently learn flow representations from CFD results.Flow DNN saves computational time by directly predicting the expected flow fields based on given flow conditions and geometry shapes.Flow DNN is the first DNN that incorporates the underlying physical conservation laws of fluid dynamics with a carefully designed attention mechanism for steady flow prediction.This approach not only improves the prediction accuracy,but also preserves the physical consistency of the predicted flow fields,which is essential for CFD.Various metrics are derived to evaluate Flow DNN with respect to the whole flow fields or regions of interest(RoIs)(e.g.,boundary layers where flow quantities change rapidly).Experiments show that Flow DNN significantly outperforms alternative methods with faster inference and more accurate results.It speeds up a graphics processing unit(GPU)accelerated CFD solver by more than 14000×,while keeping the prediction error under 5%.

关键词： Deep neural network Flow prediction Attention mechanism Physics-informed loss

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Modeling high-speed cutting of SiC_(p)/Al composites using a semi-phenomenologically based damage model

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Chinese Journal of Aeronautics 2021年第8期34卷 218-229页

作者： Junfeng xiang Lijing XIE Feinong gao School of Civil Aviation Northwestern Polytechnical UniversityXi'an 710072China Key Laboratory of Fundamental Science for Advanced Machining Beijing Institute of TechnologyBeijing 100081China

In this paper,we attempts to investigate cutting mechanisms in high-speed cutting of Al6061/Si C_(p)/15p composites using a semi-phenomenologically based damage model in the equivalent homogeneous material(EHM)framework.By combining macroscale EHM modeling and underlying microscale physical mechanisms,a feasible semi-phenomenological plastic model is proposed for prediction of cutting forces and chip morphology during high-speed turning Al6061/Si C_(p)/15p composites.This model incorporates the modified Weibull weakest-link effect to represent the strain-based damage evolution in large deformations.This proposed semi-phenomenological constitutive model is implemented by compiling material subroutines into cutting finite element(FE)codes.The effects of the critical shear stresses on chip formation that depend on the toolchip frictional coefficient are accounted for in the cutting FE model.The chip formation mechanism affecting material removal behaviors during high-speed turning is further investigated.The capabilities of the proposed constitutive model are evaluated by comparing cutting forces and chip morphologies between experiments and simulations at different cutting speeds associated with strain rates.The EHM-based and microstructure-based models are further compared in both computational efficiency and accuracy.The simulation results show that the developed semiphenomenological constitutive formalism and cutting model are promising and efficient tools for further investigation of dynamic mechanical and cutting behaviors of particle-reinforced composites with different volume fraction and particle size.

关键词： Chip morphology Damage evolution High-speed cutting Semi-phenomenological plasticity SiC_(p)/Al composites

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