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NUMERICAL STUDY ON THE PURIFICATION PERFORMANCE OF RIVERBANK

Journal of Hydrodynamics 2007年第5期19卷 643-652页

作者： dai yu wang de-guan College of Environmental Science and Engineering Hohai University Nanjing 210098 China

During the rain time, the runoff infiltrates into the riverbank through the collecting gutter and slope surface. The city runoff is generally polluted by organic, oil, heavy metal particulates, etc. The pollutants moving with the water through the riverbank experience advection, dispersion, diffusion, adsorption, biochemical reaction and plant uptaking processes. In this article, a mathematical model was developed to simulate the performance of pollutant removal of the riverbank. The model took those main mechanisms into account. The modified Richards equation was used in simulating flow field. The mass balance law was employed in deriving the equation for pollutant transport, where the diffusion and dispersion were described with the Fick-type law, the adsorption was macroscopically expressed as form isotherm, and the bio-chemical degradation process was assumed to follow the Monod kinetics. The NH3-N and TP were considered in the present model. The mathematical model was descritized with a finite element numerical model, which was applied to two types of model riverbanks. In the model test, the hydraulic loading was assumed to have the intermittent pattern simulating the storm runoff of certain return period, and the values of the rainfall runoff and concentrations of the NH3-N and TP were taken from the model test. The computed overall removal rates for the NH3-N and TP in 6 cases are in the range of 88%-98%, 87%-97%, respectively. The differences between the computed and tested overall removal rates for the NH3-N and TP are less than 5%. The time-varying oscillation pattern of the concentrations of the NH3-N and TP were rationally simulated, which shows that the model presented in this article can be used to assess the purification performance of the riverbank constructed with sand or soil.

关键词： riverbank numerical modelling purification,pollutant experiments

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Construction personnel dress code detection based on YOLO framework

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CAAI Transactions on Intelligence Technology 2024年第3期9卷 709-721页

作者： yunkai Lyu Xiaobing Yang Ai guan Jingwen wang Leni dai College of Information Engineering China Jiliang UniversityHangzhouChina College of Integrated Circuit Science and Engineering Nanjing University of Posts and TelecommunicationsNanjingChina China Jiliang University HangzhouZhejiangChina department of Mathematics University of California San DiegoLa JollaCaliforniaUSA

It is important for construction personnel to observe the dress code,such as the correct wearing of safety helmets and reflective vests is conducive to protecting the workers'lives and safety of construction.A YOLO network-based detection algorithm is proposed for the construction personnel dress code(YOLO-CPDC).Firstly,Multi-Head Self-Attention(MHSA)is introduced into the backbone network to build a hybrid back-bone,called Convolution MHSA Network(CMNet).The CMNet gives the model a global field of view and enhances the detection capability of the model for small and obscured ***,an efficient and lightweight convolution module is *** is named Ghost Shuffle Attention-Conv-BN-SiLU(GSA-CBS)and is used in the neck *** GSANeck network reduces the model size without affecting the ***,the SIoU is used in the loss function and Soft NMS is used for *** results on the self-constructed dataset show that YOLO-CPDC algorithm has higher detection accuracy than current ***-CPDC achieves a mAP50 of 93.6%.Compared with the YOLOv5s,the number of parame-ters of our model is reduced by 18%and the mAP50 is improved by 1.1%.Overall,this research effectively meets the actual demand of dress code detection in construction scenes.

关键词： artificial intelligence computer vision deep learning deep neural networks

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Prenatal amoxicillin exposure induces developmental toxicity in fetal mice and its characteristics

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Journal of Environmental Sciences 2024年第3期137卷 287-301页

作者： Yongguo dai yu Peng Wen Hu Yi Liu Hui wang department of Pharmacology Wuhan University School of Basic Medical SciencesWuhan 430071China department of Pharmacy Zhongnan Hospital of Wuhan UniversityWuhan 430071China Hubei Provincial Key Laboratory of developmentally Originated Disease Wuhan 430071China

Amoxicillin,a widely used antibiotic in human and veterinary pharmaceuticals,is now considered as an“emerging contaminant”because it exists widespreadly in the environment and brings a series of adverse ***,systematic studies about the developmental toxicity of amoxicillin are still *** explored the potential effects of amoxicillin exposure on pregnancy outcomes,maternal/fetal serum phenotypes,and fetal multiple organ development in mice,at different doses(75,150,300 mg/(kg·day))during late-pregnancy,or at a dose of 300 mg/(kg·day)during different stages(mid-/latepregnancy)and courses(single-/multi-course).Results showed that prenatal amoxicillin exposure(PAmE)had no significant infuence on the body weights of dams,but it could inhibit the physical development and reduce the survival rate of fetuses,especially during the ***,PAmE altered multiple maternal/fetal serum phenotypes,especially in *** multi-organ function results showed that PAmE inhibited testicular/adrenal steroid synthesis,long bone/cartilage and hippocampal development,and enhanced ovarian steroid synthesis and hepatic glycogenesis/lipogenesis,and the order of severity might be gonad(testis,ovary)>liver>*** analysis found that PAmE-induced multiorgan developmental and functional alterations had differences in stages,courses and fetal gender,and the most obvious changes might be in high-dose,late-pregnancy and multicourse,but there was no typical rule of a dose-response *** conclusion,this study confirmed that PAmE could cause abnormal development and multi-organ function alterations,which deepens our understanding of the risk of PAmE and provides an experimental basis for further exploration of the long-term harm.

关键词： Amoxicillin Prenatal exposure Fetal development Organ function developmental toxicity

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Effect of Mn addition on microstructure and mechanical properties of GX40CrNiSi25-12 austenitic heat resistant steel

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China Foundry 2024年第3期21卷 205-212页

作者： guan-yu Jiang Meng-wu Wu Xiao-guang Yang Hui wang yu-yuan Zhu Hubei Key Laboratory of Advanced Technology for Automotive Components Wuhan University of TechnologyWuhan 430070China Hubei Longzhong Laboratory Xiangyang 441000HubeiChina Wescast Industries(China)Co. Ltd.Wuhan 430100China

Three types of steels were designed on the basis of GX40CrNiSi25-12 austenitic heat resistant steel by adding different Mn contents(2wt.%,6wt.%,and 12wt.%).Thermodynamic calculation,microstructure characterization and mechanical property tests were conducted to investigate the effect of Mn addition on the microstructure and mechanical properties of the austenitic heat resistant *** show that the matrix structure in all the three types of steels at room temperature is completely *** NbC and M_(23)C_(6)precipitate at grain boundaries of austenite *** the increase of Mn content,the number of carbides increases and their distribution becomes more *** the Mn content increases from 1.99%to 12.06%,the ultimate tensile strength,yield strength and elongation increase by 14.6%,8.0%and 46.3%,*** improvement of the mechanical properties of austenitic steels can be explained by utilizing classic theories of alloy strengthening,including solid solution strengthening,precipitation strengthening,and grain *** increase in alloy strength can be attributed to solid solution strengthening and precipitation strengthening caused by the addition of *** improvement of the plasticity of austenitic steels can be explained from two aspects:grain refinement and homogenization of precipitated phases.

关键词： austenitic heat resistant steel manganese microstructure mechanical properties

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An experimental study on effects of temperature gradient on microstructure of a 308L stainless steel manufactured by directed energy deposition

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Journal of Iron and Steel Research International 2024年第8期31卷 2031-2040页

作者： Ting dai de-yu Gu yu-wen Qiu Wei Guo Hui Ding Yi-wei Sun School of Materials Science and Engineering Jiangsu Key Laboratory of Advanced Metallic MaterialsSoutheast UniversityNanjing 211189JiangsuChina

The effect of spatial temperature gradient on the microstructural evolution of a 308L stainless steel during the directed energy deposition(deD)process was experimentally investigated.A novel cooling system was designed and incorporated to a deD system in order to control the temperature gradient along the deposition direction during *** deposition,the workpiece was placed on a lifting platform,and as the deposition process proceeded,the platform and workpiece were gradually lowered into cooling water so that the temperature gradient along the deposition direction could be controlled and maintained stable during the deposition *** microstructure characterization results indicated that a deposition strategy with higher G and G/R values(where G is temperature gradient and R is solidification rate)produced finer cellular grains that were better aligned with the deposition direction,while a deposition strategy with lower G and G/R values produced columnar grains with larger primary arm spacing and less aligned with the deposition direction.

关键词： Additive manufacturing Directed energy deposition Stainless steel Microstructure Temperature gradient

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Multi-scale data joint inversion of minerals and porosity in altered igneous reservoirs—A case study in the South China Sea

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Petroleum Science 2024年第1期21卷 206-220页

作者： Xin-Ru wang Bao-Zhi Pan yu-Hang Guo Qing-Hui wang Yao guan College of Geo-exploration Science and Technology Jilin UniversityChangchun130046JilinChina Research Institute CNOOC Ltd.-ShenzhenShenzhen518000GuangdongChina

There are abundant igneous gas reservoirs in the South China Sea with significant value of research,and lithology classification,mineral analysis and porosity inversion are important links in reservoir ***,affected by the diverse lithology,complicated mineral and widespread alteration,conventional logging lithology classification and mineral inversion become considerably *** the same time,owing to the limitation of the wireline log response equation,the quantity and accuracy of minerals can hardly meet the exploration requirements of igneous *** overcome those issues,this study takes the South China Sea as an example,and combines multi-scale data such as micro rock slices,petrophysical experiments,wireline log and element cutting log to establish a set of joint inversion methods for minerals and porosity of altered igneous ***,we define the lithology and mineral characteristics through core slices and mineral data,and establish an igneous multi-mineral volumetric *** we determine element cutting log correction method based on core element data,and combine wireline log and corrected element cutting log to perform the lithology classification and joint inversion of minerals and ***,it is always difficult to determine the elemental eigenvalues of different minerals in *** paper uses multiple linear regression methods to solve this ***,an integrated inversion technique for altered igneous formations was *** results show that the corrected element cutting log are in good agreement with the core element data,and the mineral and porosity results obtained from the joint inversion based on the wireline log and corrected element cutting log are also in good agreement with the core data from X-ray *** results demonstrate that the inversion technique is applicable and this study provides a new direction for the mineral inversion research of altered igneous formation

关键词： Joint inversion Altered igneous rock Element correction method Lithology identification Multi mineral volume model

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A hybrid physics-informed data-driven neural network for CO_(2) storage in depleted shale reservoirs

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Petroleum Science 2024年第1期21卷 286-301页

作者： Yan-Wei wang Zhen-Xue dai Gui-Sheng wang Li Chen yu-Zhou Xia yu-Hao Zhou College of Construction Engineering Jilin UniversityChangchun130026JilinChina Institute of Intelligent Simulation and Early Warning for Subsurface Environment Jilin UniversityChangchun130026JilinChina School of Energy Resources China University of GeosciencesBeijing100083China department of Safety Environmental Protection and Quality ManagementShengli OilfieldSinopecDongying257000ShandongChina Key Laboratory of Thermo-Fluid Science and Engineering of MOE School of Energy and Power EngineeringXi'an Jiaotong UniversityXi'an710049ShaanxiChina College of Computer Science and Technology China University of Petroleum(East China)Qingdao266580ShandongChina department of Physics University of FribourgFribourg1700Switzerland

To reduce CO_(2) emissions in response to global climate change,shale reservoirs could be ideal candidates for long-term carbon geo-sequestration involving multi-scale transport ***,most current CO_(2) sequestration models do not adequately consider multiple transport ***,the evaluation of CO_(2) storage processes usually involves laborious and time-consuming numerical simulations unsuitable for practical prediction and *** this paper,an integrated model involving gas diffusion,adsorption,dissolution,slip flow,and Darcy flow is proposed to accurately characterize CO_(2) storage in depleted shale reservoirs,supporting the establishment of a training *** this basis,a hybrid physics-informed data-driven neural network(HPDNN)is developed as a deep learning surrogate for prediction and *** incorporating multiple sources of scientific knowledge,the HPDNN can be configured with limited simulation resources,significantly accelerating the forward and inversion ***,the HPDNN can more intelligently predict injection performance,precisely perform reservoir parameter inversion,and reasonably evaluate the CO_(2) storage capacity under complicated *** validation and test results demonstrate that the HPDNN can ensure high accuracy and strong robustness across an extensive applicability range when dealing with field data with multiple noise *** study has tremendous potential to replace traditional modeling tools for predicting and making decisions about CO_(2) storage projects in depleted shale reservoirs.

关键词： deep learning Physics-informed data-driven neural network depleted shale reservoirs CO_(2)storage Transport mechanisms

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A double-network porous hydrogel based on high internal phase emulsions as a vehicle for potassium sucrose octasulfate delivery accelerates diabetic wound healing

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Regenerative Biomaterials 2024年第4期3卷 82-97页

作者： Zhiwei wang Lingshun Sun Weixing wang Zheng wang Ge Shi Honglian dai Aixi yu department of Orthopedics Trauma and Microsurgery Zhongnan Hospital of Wuhan UniversityWuhan 430070China State Key Laboratory of Advanced Technology for Materials Synthesis and Processing Biomedical Materials and Engineering Research Center of Hubei ProvinceWuhan University of TechnologyWuhan 430070China

Diabetic wounds are a difficult medical *** secretion of matrix metalloproteinase-9(MMP-9)in diabetic wounds further degrades the extracellular matrix and growth factors and causes severe vascular damage,which seriously hinders diabetic wound *** solve these issues,a double-network porous hydrogel composed of poly(methyl methacrylate-co-acrylamide)(p(MMA-co-AM))and polyvinyl alcohol(PVA)was constructed by the high internal phase emulsion(HIPE)technique for the delivery of potassium sucrose octasulfate(PSO),a drug that can inhibit MMPs,increase angiogenesis and improve *** hydrogel possessed a typical polyHIPE hierarchical microstructure with interconnected porous morphologies,high porosity,high specific surface area,excellent mechanical properties and suitable swelling ***,the p(MMA-co-AM)/PVA@PSO hydrogel showed high drug-loading performance and effective PSO *** addition,both in vitro and in vivo studies showed that the p(MMA-co-AM)/PVA@PSO hydrogel had good biocompatibility and significantly accelerated diabetic wound healing by inhibiting excessive MMP-9 in diabetic wounds,increasing growth factor secretion,improving vascularization,increasing collagen deposition and promoting ***,this study provided a reliable therapeutic strategy for diabetic wound healing,some theoretical basis and new insights for the rational design and preparation of wound hydrogel dressings with high porosity,high drug-loading performance and excellent mechanical properties.

关键词： high internal phase emulsions double-network porous hydrogel drug delivery diabetic wound healing sucrose octasulfate

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Enhancing cut selection through reinforcement learning

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Science China Mathematics 2024年第6期67卷 1377-1394页

作者： Shengchao wang Liang Chen Lingfeng Niu yu-Hong dai Academy of Mathematics and Systems Science Chinese Academy of SciencesBeijing100190China Research Center on Fictitious Economy and Data Science Chinese Academy of SciencesBeijing100190China

With the rapid development of artificial intelligence in recent years,applying various learning techniques to solve mixed-integer linear programming(MILP)problems has emerged as a burgeoning research *** from constructing end-to-end models directly,integrating learning approaches with some modules in the traditional methods for solving MILPs is also a promising *** cutting plane method is one of the fundamental algorithms used in modern MILP solvers,and the selection of appropriate cuts from the candidate cuts subset is crucial for enhancing *** to the reliance on expert knowledge and problem-specific heuristics,classical cut selection methods are not always transferable and often limit the scalability and generalizability of the cutting plane *** provide a more efficient and generalizable strategy,we propose a reinforcement learning(RL)framework to enhance cut selection in the solving process of ***,we design feature vectors to incorporate the inherent properties of MILP and computational information from the solver and represent MILP instances as bipartite ***,we choose the weighted metrics to approximate the proximity of feasible solutions to the convex hull and utilize the learning method to determine the weights assigned to each ***,a graph convolutional neural network is adopted with a self-attention mechanism to predict the value of weighting ***,we transform the cut selection process into a Markov decision process and utilize RL method to train the *** experiments are conducted based on a leading open-source MILP solver *** on both general and specific datasets validate the effectiveness and efficiency of our proposed approach.

关键词： reinforcement learning mixed-integer linear programming cutting plane method cut selection

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Grating-free autofocus for single-pixel microscopic imaging

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Photonics Research 2024年第6期12卷 1313-1321页

作者： guan wang HUAXIA deNG yu CAI MENGCHAO MA XIANG ZHONG XINGLONG GONG CAS Key Laboratory of Mechanical Behavior and design of Materials Department of Modern MechanicsUniversity of Science and Technology of ChinaHefei 230027China School of Instrument Science and Opto-electronics Engineering Hefei University of TechnologyHefei 230009China

As a computational technology,single-pixel microscopic imaging(SPMI)transfers the target’s spatial information into a temporal *** traditional focusing method of imaging before evaluation is not applicable to the SPMI *** propose a grating-free autofocus strategy derived from the physical mechanism of optical *** the amplitude information of just one high-frequency point in the spectrum is all that is needed to achieve fast autofocus with the SPMI ***,only four patterns need to be cyclically projected,enabling efficient localization of the focal plane based on the measurement *** demonstrate SPMI autofocus experiments at micrometer and even nanometer depths of *** proposed method can be extended to achieve SMPI autofocus with invisible optical pattern illumination.

关键词： optical system illumination

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