The liquid loading is one of the most frequently encountered phenomena in the transportation of gas pipeline,reducing the transmission efficiency and threatening the flow assurance.However,most of the traditional mech...The liquid loading is one of the most frequently encountered phenomena in the transportation of gas pipeline,reducing the transmission efficiency and threatening the flow assurance.However,most of the traditional mechanism models are semi-empirical models,and have to be resolved under different working conditions with complex calculation process.The development of big data technology and artificial intelligence provides the possibility to establish data-driven models.This paper aims to establish a liquid loading prediction model for natural gas pipeline with high generalization ability based on machine learning.First,according to the characteristics of actual gas pipeline,a variety of reasonable combinations of working conditions such as different gas velocity,pipe diameters,water contents and outlet pressures were set,and multiple undulating pipeline topography with different elevation differences was established.Then a large number of simulations were performed by simulator OLGA to obtain the data required for machine learning.After data preprocessing,six supervised learning algorithms,including support vector machine(SVM),decision tree(DT),random forest(RF),artificial neural network(ANN),plain Bayesian classification(NBC),and K nearest neighbor algorithm(KNN),were compared to evaluate the performance of liquid loading prediction.Finally,the RF and KNN with better performance were selected for parameter tuning and then used to the actual pipeline for liquid loading location prediction.Compared with OLGA simulation,the established data-driven model not only improves calculation efficiency and reduces workload,but also can provide technical support for gas pipeline flow assurance.展开更多
AIM:To describe the multimodal imaging features,treatment,and outcomes of patients diagnosed with adultonset Coats disease.METHODS:This retrospective study included patients first diagnosed with Coats disease at≥18 y...AIM:To describe the multimodal imaging features,treatment,and outcomes of patients diagnosed with adultonset Coats disease.METHODS:This retrospective study included patients first diagnosed with Coats disease at≥18 years of age between September 2017 and September 2021.Some patients received anti-vascular endothelial growth factor(VEGF)therapy(conbercept,0.5 mg)as the initial treatment,which was combined with laser photocoagulation as needed.All the patients underwent best corrected visual acuity(BCVA)and intraocular pressure examinations,fundus color photography,spontaneous fluorescence tests,fundus fluorescein angiography,optical coherence tomography(OCT),OCT angiography,and other examinations.BCVA alterations and multimodal image findings in the affected eyes following treatment were compared and the prognostic factors were analyzed.RESULTS:The study included 15 patients who were aged 24-72(57.33±12.61)y at presentation.Systemic hypertension was the most common associated systemic condition,occurring in 13(86.7%)patients.Baseline BCVA ranged from 2.0 to 5.0(4.0±1.1),which showed improvement following treatment(4.2±1.0).Multimodal imaging revealed retinal telangiectasis in 13 patients(86.7%),patchy hemorrhage in 5 patients(33.3%),and stage 2B disease(Shield’s staging criteria)in 11 patients(73.3%).OCT revealed that the baseline central macular thickness(CMT)ranged from 129 to 964μm(473.0±230.1μm),with 13 patients(86.7%)exhibiting a baseline CMT exceeding 250μm.Furthermore,8 patients(53.3%)presented with an epiretinal membrane at baseline or during follow-up.Hyper-reflective scars were observed on OCT in five patients(33.3%)with poor visual prognosis.Vision deteriorated in one patient who did not receive treatment.Final vision was stable in three patients who received laser treatment,whereas improvement was observed in one of two patients who received anti-VEGF therapy alone.In addition,8 of 9 patients(88.9%)who received laser treatment and conbercept exhibited stable or improved BCVA.CONCLUSION:Multimodal imaging can help diagnose adult-onset Coats disease.Anti-VEGF treatment combined with laser therapy can be an option for improving or maintaining BCVA and resolving macular edema.The final visual outcome depends on macular involvement and the disease stage.展开更多
High-performance epoxy(EP)composites with excellent thermal conductivity and dielectric properties have attracted increasing attention for effective thermal management.In this work,three-dimensional(3D)structural func...High-performance epoxy(EP)composites with excellent thermal conductivity and dielectric properties have attracted increasing attention for effective thermal management.In this work,three-dimensional(3D)structural functional fillers were prepared by an electrostatic self-assembly approach.The negatively charged carbon nanotubes(nCNTs)prepared by carboxylation on the surface of CNTs were attached to the positively charged boron nitride(pBN)to form the 3D pBN@nCNTs functional fillers.The morphological characterizations of the formed 3D pBN@nCNTs fillers and epoxy composites were established,illustrating that nCNTs were linearly overlapped between the BN sheets,thus forming a 3D heat conduction network in the epoxy matrix.The synergistic effect of pBN with nCNTs on the enhancement of thermal conductivity and dielectric properties of composites was systematically studied.The experimental results demonstrated that the thermal conductivity of pBN@nCNTs/EP composites could reach 1.986 W m1K1 with the loading of 50 wt%fillers at 10:1 mass ratio of pBN:nCNTs,which is 464%and 124%higher than that of pure EP and BN/EP,respectively.Simultaneously,the dielectric permittivity was successfully increased to 15.14.Moreover,the thermal stability of the composites was synchronously enhanced.This study provides a facile path to fabricate thermosetting polymer composites with high thermal conductivity and dielectric properties.展开更多
基金supported by the National Science and Technology Major Project of China(2016ZX05066005-001)Zhejiang Province Key Research and Development Plan(2021C03152)Zhoushan Science and Technology Project(2021C21011)
文摘The liquid loading is one of the most frequently encountered phenomena in the transportation of gas pipeline,reducing the transmission efficiency and threatening the flow assurance.However,most of the traditional mechanism models are semi-empirical models,and have to be resolved under different working conditions with complex calculation process.The development of big data technology and artificial intelligence provides the possibility to establish data-driven models.This paper aims to establish a liquid loading prediction model for natural gas pipeline with high generalization ability based on machine learning.First,according to the characteristics of actual gas pipeline,a variety of reasonable combinations of working conditions such as different gas velocity,pipe diameters,water contents and outlet pressures were set,and multiple undulating pipeline topography with different elevation differences was established.Then a large number of simulations were performed by simulator OLGA to obtain the data required for machine learning.After data preprocessing,six supervised learning algorithms,including support vector machine(SVM),decision tree(DT),random forest(RF),artificial neural network(ANN),plain Bayesian classification(NBC),and K nearest neighbor algorithm(KNN),were compared to evaluate the performance of liquid loading prediction.Finally,the RF and KNN with better performance were selected for parameter tuning and then used to the actual pipeline for liquid loading location prediction.Compared with OLGA simulation,the established data-driven model not only improves calculation efficiency and reduces workload,but also can provide technical support for gas pipeline flow assurance.
文摘AIM:To describe the multimodal imaging features,treatment,and outcomes of patients diagnosed with adultonset Coats disease.METHODS:This retrospective study included patients first diagnosed with Coats disease at≥18 years of age between September 2017 and September 2021.Some patients received anti-vascular endothelial growth factor(VEGF)therapy(conbercept,0.5 mg)as the initial treatment,which was combined with laser photocoagulation as needed.All the patients underwent best corrected visual acuity(BCVA)and intraocular pressure examinations,fundus color photography,spontaneous fluorescence tests,fundus fluorescein angiography,optical coherence tomography(OCT),OCT angiography,and other examinations.BCVA alterations and multimodal image findings in the affected eyes following treatment were compared and the prognostic factors were analyzed.RESULTS:The study included 15 patients who were aged 24-72(57.33±12.61)y at presentation.Systemic hypertension was the most common associated systemic condition,occurring in 13(86.7%)patients.Baseline BCVA ranged from 2.0 to 5.0(4.0±1.1),which showed improvement following treatment(4.2±1.0).Multimodal imaging revealed retinal telangiectasis in 13 patients(86.7%),patchy hemorrhage in 5 patients(33.3%),and stage 2B disease(Shield’s staging criteria)in 11 patients(73.3%).OCT revealed that the baseline central macular thickness(CMT)ranged from 129 to 964μm(473.0±230.1μm),with 13 patients(86.7%)exhibiting a baseline CMT exceeding 250μm.Furthermore,8 patients(53.3%)presented with an epiretinal membrane at baseline or during follow-up.Hyper-reflective scars were observed on OCT in five patients(33.3%)with poor visual prognosis.Vision deteriorated in one patient who did not receive treatment.Final vision was stable in three patients who received laser treatment,whereas improvement was observed in one of two patients who received anti-VEGF therapy alone.In addition,8 of 9 patients(88.9%)who received laser treatment and conbercept exhibited stable or improved BCVA.CONCLUSION:Multimodal imaging can help diagnose adult-onset Coats disease.Anti-VEGF treatment combined with laser therapy can be an option for improving or maintaining BCVA and resolving macular edema.The final visual outcome depends on macular involvement and the disease stage.
基金National Key Research and Development Program of China(2017YFB0903804)Science and Technology Program of the State Grid Corporation of China(No.5455DW170026).
文摘High-performance epoxy(EP)composites with excellent thermal conductivity and dielectric properties have attracted increasing attention for effective thermal management.In this work,three-dimensional(3D)structural functional fillers were prepared by an electrostatic self-assembly approach.The negatively charged carbon nanotubes(nCNTs)prepared by carboxylation on the surface of CNTs were attached to the positively charged boron nitride(pBN)to form the 3D pBN@nCNTs functional fillers.The morphological characterizations of the formed 3D pBN@nCNTs fillers and epoxy composites were established,illustrating that nCNTs were linearly overlapped between the BN sheets,thus forming a 3D heat conduction network in the epoxy matrix.The synergistic effect of pBN with nCNTs on the enhancement of thermal conductivity and dielectric properties of composites was systematically studied.The experimental results demonstrated that the thermal conductivity of pBN@nCNTs/EP composites could reach 1.986 W m1K1 with the loading of 50 wt%fillers at 10:1 mass ratio of pBN:nCNTs,which is 464%and 124%higher than that of pure EP and BN/EP,respectively.Simultaneously,the dielectric permittivity was successfully increased to 15.14.Moreover,the thermal stability of the composites was synchronously enhanced.This study provides a facile path to fabricate thermosetting polymer composites with high thermal conductivity and dielectric properties.
