As oil and gas exploration moves into deeper waters,marine risers are subjected to increasingly complex service conditions,including vessel motions,ocean currents,seabed-soil interactions,and internal flow effects.Thi...As oil and gas exploration moves into deeper waters,marine risers are subjected to increasingly complex service conditions,including vessel motions,ocean currents,seabed-soil interactions,and internal flow effects.This work establishes a dynamic behavior model of steel catenary risers(SCRs)with varying curvatures subjected to internal flow and external currents and considers the effects of pipe-soil interactions on the curvature profile.The governing equation is solved via the generalized integral transform technique(GITT),which yields a semi-analytical solution of a high-order nonlinear partial differential equation.Parametric studies are then performed to analyze the effects of varying curvature on the vibration frequency and amplitude of SCRs.The vibration frequency and amplitude increase with the touchdown angle and hang-off angle,although the effect of the hang-off angle is negligible.Additionally,as the curvature increases along the centerline axis,the position of the maximum amplitude of the SCR moves upward.展开更多
Many catalysts have shown excellent activity for the sulfur reduction reaction(SRR),but sluggish electrochemistry kinetics have hindered the development of lithium-sulfur batteries.It has been found that the activity ...Many catalysts have shown excellent activity for the sulfur reduction reaction(SRR),but sluggish electrochemistry kinetics have hindered the development of lithium-sulfur batteries.It has been found that the activity of catalysts for the sulfur evolution reaction(SER)plays a crucial role in determining the overall reaction kinetics.To address this issue,the rational design of catalysts is crucial.Here,we proposed a popular rule to accelerate SER by using chip-like high-entropy perovskite oxide La_(0.7)Sr_(0.3)(Fe_(0.2)Co_(0.2)Ni_(0.2)Zn_(0.2)Mn_(0.2))O_(3-δ)(LMO-HEO)as advanced electrocatalysts.The strong interaction between the adjacent metal atoms in different metals of LMO-HEO electrocatalysts could lead to a"cocktail effect",which not only greatly improved the catalytic capacity toward sulfur species,but also accelerated the oxidation reaction kinetics of Li_2S.As a result,the S/La_(0.7)Sr_(0.3)(Fe_(0.2)Co_(0.2)Ni_(0.2)Zn_(0.2))Mn_(0.2)O_(3-δ)cathodes delivered excellent cyclic stability with a capacity decay of only 0.025%after 1200 cycles at 2 C.This work has provided a rational design idea for new multifunctional electrocatalysts with high catalytic capacity.展开更多
For Ti-6Al-4V,a titanium alloy increasingly used in aerospace structure,selective laser melting(SLM)is an attractive additive manufacturing technology,which is attributed to its complex construction capability with hi...For Ti-6Al-4V,a titanium alloy increasingly used in aerospace structure,selective laser melting(SLM)is an attractive additive manufacturing technology,which is attributed to its complex construction capability with high accuracy and good surface quality.In order to obtain qualified mechanical properties,SLM parameters and post processing should be tailored for diverse service conditions.Fracture toughness and fatigue crack growth(FCG)behavior are critical characteristics for damage tolerance evaluation of such metallic structures,and they are affected by post processing technologies significantly.The objective of this study is to obtain the fracture toughness and fatigue crack growth behavior of Ti-6Al-4V manufactured by SLM,and to evaluate the influence of post-SLM thermomechanical treatment and surface machining.Fracture toughness and FCG tests were performed for SLM Ti-6Al-4V in three types of post processing status:as-built,heat treated and hot isostatically pressed(HIPed),respectively.Specimens with as-built and machined surface were tested.The microstructure and fractography were analyzed as well in order to investigate the relevance among manufacture process,microstructure and mechanical properties.The results demonstrate that as-built SLM Ti-6Al-4V presents poor ductility and FCG behavior due to martensitic microstructure and residual stresses.Both heat treatment and hot isostatic pressing improve the plane-stress fracture toughness and FCG performance considerably,while surface machining shows slight effect.展开更多
A marine riser,one of the most important components of offshore oil/gas transportation,needs to be designed to eliminate the risks caused by complex ocean environments,platform displacement and internal corrosion,etc....A marine riser,one of the most important components of offshore oil/gas transportation,needs to be designed to eliminate the risks caused by complex ocean environments,platform displacement and internal corrosion,etc.In this study,a new analytical-numerical assessment approach is proposed in order to quantitatively investigate the reliability of internally corroded risers under combined loads including axial tension and internal pressure.First,an analytical solution of the limit state function of intact risers under combined loads is obtained,which is further modified by the non-dimensional corrosion depth （d/ t） for the risers with a narrow and long corrosion defect.The relationship between d/t and limited internal pressure is obtained by finite element analysis and nonlinear regression.Through an advanced first-order reliability method （HL-RF） algorithm,reliability analysis is performed to obtain the failure probability,the reliability index and the sensitivity.These results are further verified by Monte-Carlo importance sampling.The proposed approach of reliability analysis provides an accurate and effective way to estimate the reliability of marine risers with narrow and long corrosion defects under combined loads.展开更多
Exploring the production and application of clean energy has always been the core of sustainable development.As a clean and sustainable technology,electrocatalysis has been receiving widespread attention.It is crucial...Exploring the production and application of clean energy has always been the core of sustainable development.As a clean and sustainable technology,electrocatalysis has been receiving widespread attention.It is crucial to achieve efficient,stable and cheap electrocatalysts.However,the traditional“trial and error”method is time-consuming,laborious and costly.In recent years,with the significant increase in computing power,computations have played an important role in electrocatalyst design.Nevertheless,it is still difficult to search for advanced electrocatalysts in the vast chemical space through traditional density functional theory(DFT)computations.Fortunately,the development of machine learning and interdisciplinary integration will inject new impetus into targeted design of electrocatalysts.Machine learning is able to predict electrochemical performances with an accuracy close to DFT.Here we provide an overview of the application of machine learning in electrocatalyst design,including the prediction of structure,thermodynamic properties and kinetic barriers.We also discuss the potential of explicit solvent model combined with machine learning molecular dynamics in this field.Finally,the favorable circumstances and challenges are outlined for the future development of machine learning in electrocatalysis.The studies on electrochemical processes by machine learning will further realize targeted design of high-efficiency electrocatalysts.展开更多
BACKGROUND： Increasing evidence indicates that down- regulation of cell adhesion molecule 1 （CADM1） contributes to tumorigenesis in various cancers. The present study was undertaken to investigate the CADM1 express...BACKGROUND： Increasing evidence indicates that down- regulation of cell adhesion molecule 1 （CADM1） contributes to tumorigenesis in various cancers. The present study was undertaken to investigate the CADM1 expression pattern in human hepatocellular carcinoma （HCC）, and to elucidate the mechanism underlying CADMl-mediated tumor suppression.展开更多
Leveraging big data analytics and advanced algorithms to accelerate and optimize the process of molecular and materials design, synthesis, and application has revolutionized the field of molecular and materials scienc...Leveraging big data analytics and advanced algorithms to accelerate and optimize the process of molecular and materials design, synthesis, and application has revolutionized the field of molecular and materials science, allowing researchers to gain a deeper understanding of material properties and behaviors,leading to the development of new materials that are more efficient and reliable. However, the difficulty in constructing large-scale datasets of new molecules/materials due to the high cost of data acquisition and annotation limits the development of conventional machine learning(ML) approaches. Knowledgereused transfer learning(TL) methods are expected to break this dilemma. The application of TL lowers the data requirements for model training, which makes TL stand out in researches addressing data quality issues. In this review, we summarize recent progress in TL related to molecular and materials. We focus on the application of TL methods for the discovery of advanced molecules/materials, particularly, the construction of TL frameworks for different systems, and how TL can enhance the performance of models. In addition, the challenges of TL are also discussed.展开更多
Fracturing fluids(FFs)have been widely used to stimulate the tight reservoir.However,current FFs will not only lose their rheological property at high temperatures and high salt but also show an incomplete gel-breakin...Fracturing fluids(FFs)have been widely used to stimulate the tight reservoir.However,current FFs will not only lose their rheological property at high temperatures and high salt but also show an incomplete gel-breaking property.Herein,a double crosslinking network FF with pretty superiorities in rheology and low damage to the core was constructed by introducing both physical crosslinking and chemical crosslinking into the system.The construction of double crosslinking networks enhanced the rheology of this functional FF.The particle sizes of gel-breaking fluids are mainly distributed in 1.0e10,000 nm;furthermore,for every 10,000 mg/L increase in salinity,the particle size of the gel-breaking fluid is decreased by almost half.The adsorption capacity(<1.0 mg/g)gradually decreased with the increase of salinity at 20℃.Moreover,the adsorption of gel-breaking fluids on the rock decreased first and then kept stable with temperature increasing at a salinity of ≤30,000 mg/L,however,showed the opposite trend at 40,000 mg/L.The results of rheology,particle size,static adsorption,and core damage showed that this functional FF could be an alternative for the stimulation of a tight reservoir with high temperature and recycling of produced water with high salinity.展开更多
This article reports the development of a novel switchable Pickering emulsion with rapid CO_(2)/N_(2) respon-siveness,which is stabilized using alumina nanoparticles hydrophobized in situ with a trace amount of a swit...This article reports the development of a novel switchable Pickering emulsion with rapid CO_(2)/N_(2) respon-siveness,which is stabilized using alumina nanoparticles hydrophobized in situ with a trace amount of a switchable superamphiphile via electrostatic interactions.With the introduction of CO_(2) for 30 s,the Pickering emulsion can be spontaneously demulsified with complete phase separation;the emulsion can then be reconstructed in response to N_(2) purging for 10 min followed by homogenization.Moreover,the stable Pickering emulsion can be stored for more than 60 days at room temperature with-out any visible change.The CO_(2)/N_(2)-responsive behavior of the switchable Pickering emulsion is attribu-ted to the reversible desorption/adsorption of the switchable surfactants on the surfaces of the alumina nanoparticles upon the alternative bubbling of CO_(2)or N_(2).Thanks to the simple fabrication of the surfac-tant and the hydrophobization of the alumina nanoparticles,this research has developed an extremely facile and cost-efficient method for preparing a rapidly CO_(2)/N_(2)-responsive switchable Pickering emul-sion.The dosage of the switchable surfactants has been significantly reduced by nearly 1500 times(from 150 to 0.1 mmol·L^(-1))as compared with the dosage used in previous studies.Moreover,the as-prepared CO_(2)/N_(2)-responsive switchable Pickering emulsion is environmentally friendly,mild,and nontoxic;thus,it holds great potential for practical applications with considerable economic and environmental benefits,such as oil transport,fossil fuel production,environmental gases detection,and the encapsulation and release of active ingredients.展开更多
In this paper,two classes of Riesz space fractional partial differential equations including space-fractional and space-time-fractional ones are considered.These two models can be regarded as the generalization of the...In this paper,two classes of Riesz space fractional partial differential equations including space-fractional and space-time-fractional ones are considered.These two models can be regarded as the generalization of the classical wave equation in two space dimensions.Combining with the Crank-Nicolson method in temporal direction,efficient alternating direction implicit Galerkin finite element methods for solving these two fractional models are developed,respectively.The corresponding stability and convergence analysis of the numerical methods are discussed.Numerical results are provided to verify the theoretical analysis.展开更多
Objective To establish a rat model of Spinal Cord Injury(SCI)with the pathopattern of Qi-deficiency and Blood-stasis(QDBS)in Traditional Chinese Medicine(TCM),and then assess its feasibility.Methods Swimming exhaustio...Objective To establish a rat model of Spinal Cord Injury(SCI)with the pathopattern of Qi-deficiency and Blood-stasis(QDBS)in Traditional Chinese Medicine(TCM),and then assess its feasibility.Methods Swimming exhaustion method and Rubrospinal Tract(RST)transection were combined to establish arat model of SCI with pathopattern of QDBS in TCM.Macroscopic representation,including the body weight,food intake and tongue scores,was recorded.Behavioristics was scored with spontaneous vertical exploration test.Hemorrheology was analyzed using hemorheological analyzer and morphology of spinal cord was observed.The feasibility of the model was confirmed on the basis of the reversion caused by administration of Bu Yang Huan Wu Decoction(BYHWD).Results The findings in the QDBS group were consistent with the symptoms of QDBS syndrome,including reduced body weight,food intake,and forelimb utilization rate and increased tongue scores.However,the corresponding findings in the BYHWD group were superior to those in the QDBS group after35d(P<0.05).In comparison with the control group,the QDBS group showed higher whole blood viscosity and hematocrit values(P<0.05)and a lower red blood cell(RBC)deformability index(P<0.05),while the corresponding findings in the BYHWD group were close to those in the control group.An eminence or induration appeared in the injured spinal cord,which was suspected to be vacuoles or a scar.Hematoxylin-eosin staining showed that the R/T ratio in the BYHWD group was higher than that in the QDBS group(P<0.05).Conclusion Swimming exhaustion method combined with RST transection operation can successfully establish a rat model of SCI with pathopattern of QDBS.展开更多
Accurate regulation of two-dimensional materials has become an effective strategy to develop a wide range of catalytic applications.The introduction of heterogeneous components has a significant impact on the performa...Accurate regulation of two-dimensional materials has become an effective strategy to develop a wide range of catalytic applications.The introduction of heterogeneous components has a significant impact on the performance of materials,which makes it difficult to discover and understand the structure-property relationships at the atomic level.Here,we developed a novel and efficient ensemble learning classifier with synthetic minority oversampling technique(SMOTE) to discover all possible arsenene catalysts with implanted heteroatoms for hydrogen evolution reaction(HER).A total of 850 doped arsenenes were collected as a database and 140 modified arsenene materials with different doping atoms and doping sites were identified as promising candidate catalysts for HER,with a machine learning prediction accuracy of 81%.Based on the results of machine learning,we proposed 13 low-cost and easily synthesized two-dimensional Fe-doped arsenene catalytic materials that are expected to contribute to high-efficient HER.The proposed ensemble method achieved high prediction accuracy,but millions of times faster to predict Gibbs free energies and only required a small amount of data.This study indicates that the presented ensemble learning classifier is capable of screening high-efficient catalysts,and can be further extended to predict other two-dimensional catalysts with delicate regulation.展开更多
基金financially supported by the National Natural Science Foundation of China(Grant No.52201312).
文摘As oil and gas exploration moves into deeper waters,marine risers are subjected to increasingly complex service conditions,including vessel motions,ocean currents,seabed-soil interactions,and internal flow effects.This work establishes a dynamic behavior model of steel catenary risers(SCRs)with varying curvatures subjected to internal flow and external currents and considers the effects of pipe-soil interactions on the curvature profile.The governing equation is solved via the generalized integral transform technique(GITT),which yields a semi-analytical solution of a high-order nonlinear partial differential equation.Parametric studies are then performed to analyze the effects of varying curvature on the vibration frequency and amplitude of SCRs.The vibration frequency and amplitude increase with the touchdown angle and hang-off angle,although the effect of the hang-off angle is negligible.Additionally,as the curvature increases along the centerline axis,the position of the maximum amplitude of the SCR moves upward.
基金partially supported by grants from the National Natural Science Foundation of China(No.52072099)Team program of the Natural Science Foundation of Heilongjiang Province,China(No.TD2021E005)Joint Guidance Project of the Natural Science Foundation of Heilongjiang Province,China(No.LH2022E093)。
文摘Many catalysts have shown excellent activity for the sulfur reduction reaction(SRR),but sluggish electrochemistry kinetics have hindered the development of lithium-sulfur batteries.It has been found that the activity of catalysts for the sulfur evolution reaction(SER)plays a crucial role in determining the overall reaction kinetics.To address this issue,the rational design of catalysts is crucial.Here,we proposed a popular rule to accelerate SER by using chip-like high-entropy perovskite oxide La_(0.7)Sr_(0.3)(Fe_(0.2)Co_(0.2)Ni_(0.2)Zn_(0.2)Mn_(0.2))O_(3-δ)(LMO-HEO)as advanced electrocatalysts.The strong interaction between the adjacent metal atoms in different metals of LMO-HEO electrocatalysts could lead to a"cocktail effect",which not only greatly improved the catalytic capacity toward sulfur species,but also accelerated the oxidation reaction kinetics of Li_2S.As a result,the S/La_(0.7)Sr_(0.3)(Fe_(0.2)Co_(0.2)Ni_(0.2)Zn_(0.2))Mn_(0.2)O_(3-δ)cathodes delivered excellent cyclic stability with a capacity decay of only 0.025%after 1200 cycles at 2 C.This work has provided a rational design idea for new multifunctional electrocatalysts with high catalytic capacity.
基金supported by the Innovation Fund of Aircraft Strength Research Institute of China(No.16-025-03)
文摘For Ti-6Al-4V,a titanium alloy increasingly used in aerospace structure,selective laser melting(SLM)is an attractive additive manufacturing technology,which is attributed to its complex construction capability with high accuracy and good surface quality.In order to obtain qualified mechanical properties,SLM parameters and post processing should be tailored for diverse service conditions.Fracture toughness and fatigue crack growth(FCG)behavior are critical characteristics for damage tolerance evaluation of such metallic structures,and they are affected by post processing technologies significantly.The objective of this study is to obtain the fracture toughness and fatigue crack growth behavior of Ti-6Al-4V manufactured by SLM,and to evaluate the influence of post-SLM thermomechanical treatment and surface machining.Fracture toughness and FCG tests were performed for SLM Ti-6Al-4V in three types of post processing status:as-built,heat treated and hot isostatically pressed(HIPed),respectively.Specimens with as-built and machined surface were tested.The microstructure and fractography were analyzed as well in order to investigate the relevance among manufacture process,microstructure and mechanical properties.The results demonstrate that as-built SLM Ti-6Al-4V presents poor ductility and FCG behavior due to martensitic microstructure and residual stresses.Both heat treatment and hot isostatic pressing improve the plane-stress fracture toughness and FCG performance considerably,while surface machining shows slight effect.
基金the National Basic Research Program of China(973 Program,Grant No.2011CB013702)the Beijing Natural Science Foundation(Grant No.KZ201210017017)
文摘A marine riser,one of the most important components of offshore oil/gas transportation,needs to be designed to eliminate the risks caused by complex ocean environments,platform displacement and internal corrosion,etc.In this study,a new analytical-numerical assessment approach is proposed in order to quantitatively investigate the reliability of internally corroded risers under combined loads including axial tension and internal pressure.First,an analytical solution of the limit state function of intact risers under combined loads is obtained,which is further modified by the non-dimensional corrosion depth （d/ t） for the risers with a narrow and long corrosion defect.The relationship between d/t and limited internal pressure is obtained by finite element analysis and nonlinear regression.Through an advanced first-order reliability method （HL-RF） algorithm,reliability analysis is performed to obtain the failure probability,the reliability index and the sensitivity.These results are further verified by Monte-Carlo importance sampling.The proposed approach of reliability analysis provides an accurate and effective way to estimate the reliability of marine risers with narrow and long corrosion defects under combined loads.
文摘Exploring the production and application of clean energy has always been the core of sustainable development.As a clean and sustainable technology,electrocatalysis has been receiving widespread attention.It is crucial to achieve efficient,stable and cheap electrocatalysts.However,the traditional“trial and error”method is time-consuming,laborious and costly.In recent years,with the significant increase in computing power,computations have played an important role in electrocatalyst design.Nevertheless,it is still difficult to search for advanced electrocatalysts in the vast chemical space through traditional density functional theory(DFT)computations.Fortunately,the development of machine learning and interdisciplinary integration will inject new impetus into targeted design of electrocatalysts.Machine learning is able to predict electrochemical performances with an accuracy close to DFT.Here we provide an overview of the application of machine learning in electrocatalyst design,including the prediction of structure,thermodynamic properties and kinetic barriers.We also discuss the potential of explicit solvent model combined with machine learning molecular dynamics in this field.Finally,the favorable circumstances and challenges are outlined for the future development of machine learning in electrocatalysis.The studies on electrochemical processes by machine learning will further realize targeted design of high-efficiency electrocatalysts.
基金supported by grants from the National S&T Major Project(2012ZX10002-017)National Natural Science Foundation of China(81201944)+1 种基金Health Science and Technology Program of Zhejiang Province(2013KYB083)Education Department of Zhejiang Province Scientific Research Project(Y201430751)
文摘BACKGROUND： Increasing evidence indicates that down- regulation of cell adhesion molecule 1 （CADM1） contributes to tumorigenesis in various cancers. The present study was undertaken to investigate the CADM1 expression pattern in human hepatocellular carcinoma （HCC）, and to elucidate the mechanism underlying CADMl-mediated tumor suppression.
基金National Key R&D Program of China (No. 2021YFC2100100)Shanghai Science and Technology Project (No. 21JC1403400, 23JC1402300)。
文摘Leveraging big data analytics and advanced algorithms to accelerate and optimize the process of molecular and materials design, synthesis, and application has revolutionized the field of molecular and materials science, allowing researchers to gain a deeper understanding of material properties and behaviors,leading to the development of new materials that are more efficient and reliable. However, the difficulty in constructing large-scale datasets of new molecules/materials due to the high cost of data acquisition and annotation limits the development of conventional machine learning(ML) approaches. Knowledgereused transfer learning(TL) methods are expected to break this dilemma. The application of TL lowers the data requirements for model training, which makes TL stand out in researches addressing data quality issues. In this review, we summarize recent progress in TL related to molecular and materials. We focus on the application of TL methods for the discovery of advanced molecules/materials, particularly, the construction of TL frameworks for different systems, and how TL can enhance the performance of models. In addition, the challenges of TL are also discussed.
基金supported by the National Natural Science Foundation of China(Grant No.52274043,Grant No.52104035,Grant No.41902303)China Postdoctoral Science Foundation(2022M712646)+3 种基金Sichuan Innovation Team Project(2022JDTD0010)Natural Science Foundation of Sichuan Province(2023NSFSC0923)Sichuan Province Regional Innovation Cooperation Project(2020YFQ0031)Open Fund(PLN 2021-04 and PLN 2020-13)of State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation(Southwest Petroleum University).
文摘Fracturing fluids(FFs)have been widely used to stimulate the tight reservoir.However,current FFs will not only lose their rheological property at high temperatures and high salt but also show an incomplete gel-breaking property.Herein,a double crosslinking network FF with pretty superiorities in rheology and low damage to the core was constructed by introducing both physical crosslinking and chemical crosslinking into the system.The construction of double crosslinking networks enhanced the rheology of this functional FF.The particle sizes of gel-breaking fluids are mainly distributed in 1.0e10,000 nm;furthermore,for every 10,000 mg/L increase in salinity,the particle size of the gel-breaking fluid is decreased by almost half.The adsorption capacity(<1.0 mg/g)gradually decreased with the increase of salinity at 20℃.Moreover,the adsorption of gel-breaking fluids on the rock decreased first and then kept stable with temperature increasing at a salinity of ≤30,000 mg/L,however,showed the opposite trend at 40,000 mg/L.The results of rheology,particle size,static adsorption,and core damage showed that this functional FF could be an alternative for the stimulation of a tight reservoir with high temperature and recycling of produced water with high salinity.
基金supported by the Natural Sciences and Engineering Research Council of Canada (NSERC)the Canada Research Chairs Program (Hongbo Zeng)the China Scholarship Council (CSC) (An Chen)
文摘This article reports the development of a novel switchable Pickering emulsion with rapid CO_(2)/N_(2) respon-siveness,which is stabilized using alumina nanoparticles hydrophobized in situ with a trace amount of a switchable superamphiphile via electrostatic interactions.With the introduction of CO_(2) for 30 s,the Pickering emulsion can be spontaneously demulsified with complete phase separation;the emulsion can then be reconstructed in response to N_(2) purging for 10 min followed by homogenization.Moreover,the stable Pickering emulsion can be stored for more than 60 days at room temperature with-out any visible change.The CO_(2)/N_(2)-responsive behavior of the switchable Pickering emulsion is attribu-ted to the reversible desorption/adsorption of the switchable surfactants on the surfaces of the alumina nanoparticles upon the alternative bubbling of CO_(2)or N_(2).Thanks to the simple fabrication of the surfac-tant and the hydrophobization of the alumina nanoparticles,this research has developed an extremely facile and cost-efficient method for preparing a rapidly CO_(2)/N_(2)-responsive switchable Pickering emul-sion.The dosage of the switchable surfactants has been significantly reduced by nearly 1500 times(from 150 to 0.1 mmol·L^(-1))as compared with the dosage used in previous studies.Moreover,the as-prepared CO_(2)/N_(2)-responsive switchable Pickering emulsion is environmentally friendly,mild,and nontoxic;thus,it holds great potential for practical applications with considerable economic and environmental benefits,such as oil transport,fossil fuel production,environmental gases detection,and the encapsulation and release of active ingredients.
基金supported by the Guangxi Natural Science Foundation[grant numbers 2018GXNSFBA281020,2018GXNSFAA138121]the Doctoral Starting up Foundation of Guilin University of Technology[grant number GLUTQD2016044].
文摘In this paper,two classes of Riesz space fractional partial differential equations including space-fractional and space-time-fractional ones are considered.These two models can be regarded as the generalization of the classical wave equation in two space dimensions.Combining with the Crank-Nicolson method in temporal direction,efficient alternating direction implicit Galerkin finite element methods for solving these two fractional models are developed,respectively.The corresponding stability and convergence analysis of the numerical methods are discussed.Numerical results are provided to verify the theoretical analysis.
基金funding support from the National Natural Science Foundation of China (No. 81302899, 81373551 and 81603512)the Key Science and Research Program of Hunan Department of Science and Technology (No. 2012TF-1005)
文摘Objective To establish a rat model of Spinal Cord Injury(SCI)with the pathopattern of Qi-deficiency and Blood-stasis(QDBS)in Traditional Chinese Medicine(TCM),and then assess its feasibility.Methods Swimming exhaustion method and Rubrospinal Tract(RST)transection were combined to establish arat model of SCI with pathopattern of QDBS in TCM.Macroscopic representation,including the body weight,food intake and tongue scores,was recorded.Behavioristics was scored with spontaneous vertical exploration test.Hemorrheology was analyzed using hemorheological analyzer and morphology of spinal cord was observed.The feasibility of the model was confirmed on the basis of the reversion caused by administration of Bu Yang Huan Wu Decoction(BYHWD).Results The findings in the QDBS group were consistent with the symptoms of QDBS syndrome,including reduced body weight,food intake,and forelimb utilization rate and increased tongue scores.However,the corresponding findings in the BYHWD group were superior to those in the QDBS group after35d(P<0.05).In comparison with the control group,the QDBS group showed higher whole blood viscosity and hematocrit values(P<0.05)and a lower red blood cell(RBC)deformability index(P<0.05),while the corresponding findings in the BYHWD group were close to those in the control group.An eminence or induration appeared in the injured spinal cord,which was suspected to be vacuoles or a scar.Hematoxylin-eosin staining showed that the R/T ratio in the BYHWD group was higher than that in the QDBS group(P<0.05).Conclusion Swimming exhaustion method combined with RST transection operation can successfully establish a rat model of SCI with pathopattern of QDBS.
基金supported by the National Key R&D Program of China(No.2021YFC2100100)the National Natural Science Foundation of China(No.21901157)the Shanghai Science and Technology Project(No.21JC1403400)。
文摘Accurate regulation of two-dimensional materials has become an effective strategy to develop a wide range of catalytic applications.The introduction of heterogeneous components has a significant impact on the performance of materials,which makes it difficult to discover and understand the structure-property relationships at the atomic level.Here,we developed a novel and efficient ensemble learning classifier with synthetic minority oversampling technique(SMOTE) to discover all possible arsenene catalysts with implanted heteroatoms for hydrogen evolution reaction(HER).A total of 850 doped arsenenes were collected as a database and 140 modified arsenene materials with different doping atoms and doping sites were identified as promising candidate catalysts for HER,with a machine learning prediction accuracy of 81%.Based on the results of machine learning,we proposed 13 low-cost and easily synthesized two-dimensional Fe-doped arsenene catalytic materials that are expected to contribute to high-efficient HER.The proposed ensemble method achieved high prediction accuracy,but millions of times faster to predict Gibbs free energies and only required a small amount of data.This study indicates that the presented ensemble learning classifier is capable of screening high-efficient catalysts,and can be further extended to predict other two-dimensional catalysts with delicate regulation.
