This study investigates the potential of Prosopis cineraria Leaves Powder(PCLP)as a biosorbent for removing lead(Pb)and zinc(Zn)from aqueous solutions,optimizing the process using Response Surface Methodology(RSM).Pro...This study investigates the potential of Prosopis cineraria Leaves Powder(PCLP)as a biosorbent for removing lead(Pb)and zinc(Zn)from aqueous solutions,optimizing the process using Response Surface Methodology(RSM).Prosopis cineraria,commonly known as Khejri,is a drought-resistant tree with significant promise in environmental applications.The research employed a Central Composite Design(CCD)to examine the independent and combined effects of key process variables,including initial metal ion concentration,contact time,pH,and PCLP dosage.RSM was used to develop mathematical models that explain the relationship between these factors and the efficiency of metal removal,allowing the determination of optimal operating conditions.The experimental results indicated that the Langmuir isotherm model was the most appropriate for describing the biosorption of both metals,suggesting favorable adsorption characteristics.Additionally,the D-R isotherm confirmed that chemisorption was the primary mechanism involved in the biosorption process.For lead removal,the optimal conditions were found to be 312.23 K temperature,pH 4.72,58.5 mg L-1 initial concentration,and 0.27 g biosorbent dosage,achieving an 83.77%removal efficiency.For zinc,the optimal conditions were 312.4 K,pH 5.86,53.07 mg L-1 initial concentration,and the same biosorbent dosage,resulting in a 75.86%removal efficiency.These findings highlight PCLP’s potential as an effective,eco-friendly biosorbent for sustainable heavy metal removal in water treatment.展开更多
Idiopathic pulmonary fibrosis(IPF)is a progressive lung disease and its incidence rate is rapidly rising.However,effective therapies for the treatment of IPF are still lacking.Phosphodiesterase 4(PDE4)inhibitors were ...Idiopathic pulmonary fibrosis(IPF)is a progressive lung disease and its incidence rate is rapidly rising.However,effective therapies for the treatment of IPF are still lacking.Phosphodiesterase 4(PDE4)inhibitors were reported to be potential anti-fibrotic agents.Herein,structure-based hit-to-lead optimization of natural isoaurostatin(8.98μmol/L)resulted in several potent inhibitors of PDE4 with half maximal inhibitory concentration(IC_(50))values ranging from 35 nmol/L to 126 nmol/L.Co-crystal structures revealed that isoaurostatin compounds exhibited different binding patterns from the classic PDE4 inhibitor rolipram and the analogues would favor to be Z configurations other than the corresponding E isomers.Finally,lead 2–9 showed remarkable in vitro/in vivo anti-fibrotic effects indicating its potential as a novel anti-IPF agent.展开更多
Due to the high-order B-spline basis functions utilized in isogeometric analysis(IGA)and the repeatedly updating global stiffness matrix of topology optimization,Isogeometric topology optimization(ITO)intrinsically su...Due to the high-order B-spline basis functions utilized in isogeometric analysis(IGA)and the repeatedly updating global stiffness matrix of topology optimization,Isogeometric topology optimization(ITO)intrinsically suffers from the computationally demanding process.In this work,we address the efficiency problem existing in the assembling stiffness matrix and sensitivity analysis using B˙ezier element stiffness mapping.The Element-wise and Interaction-wise parallel computing frameworks for updating the global stiffness matrix are proposed for ITO with B˙ezier element stiffness mapping,which differs from these ones with the traditional Gaussian integrals utilized.Since the explicit stiffness computation formula derived from B˙ezier element stiffness mapping possesses a typical parallel structure,the presented GPU-enabled ITO method can greatly accelerate the computation speed while maintaining its high memory efficiency unaltered.Numerical examples demonstrate threefold speedup:1)the assembling stiffness matrix is accelerated by 10×maximumly with the proposed GPU strategy;2)the solution efficiency of a sparse linear system is enhanced by up to 30×with Eigen replaced by AMGCL;3)the efficiency of sensitivity analysis is promoted by 100×with GPU applied.Therefore,the proposed method is a promising way to enhance the numerical efficiency of ITO for both single-patch and multiple-patch design problems.展开更多
Rockburst is a common dynamic geological hazard,frequently occurring in underground engineering(e.g.,TBM tunnelling and deep mining).In order to achieve rockburst monitoring and warning,the microseismic moni-toring te...Rockburst is a common dynamic geological hazard,frequently occurring in underground engineering(e.g.,TBM tunnelling and deep mining).In order to achieve rockburst monitoring and warning,the microseismic moni-toring technique has been widely used in the field.However,the microseismic source location has always been a challenge,playing a vital role in the precise prevention and control of rockburst.To this end,this study proposes a novel microseismic source location model that considers the anisotropy of P-wave velocity.On the one hand,it assigns a unique P-wave velocity to each propagation path,abandoning the assumption of a homogeneous ve-locity field.On the other hand,it treats the P-wave velocity as a co-inversion parameter along with the source location,avoiding the predetermination of P-wave velocity.To solve this model,three various metaheuristic multi-objective optimization algorithms are integrated with it,including the whale optimization algorithm,the butterfly optimization algorithm,and the sparrow search algorithm.To demonstrate the advantages of the model in terms of localization accuracy,localization efficiency,and solution stability,four blasting cases are collected from a water diversion tunnel project in Xinjiang,China.Finally,the effect of the number of involved sensors on the microseismic source location is discussed.展开更多
【目的】分析了ISO 55013:2024 Asset management—Guidance on the management of data assets国际标准的主要内容,该标准阐释了将数据视为资产予以有效管理的重要性,为数据资产管理体系建设提供系统性指导。【方法】通过阐述ISO 5501...【目的】分析了ISO 55013:2024 Asset management—Guidance on the management of data assets国际标准的主要内容,该标准阐释了将数据视为资产予以有效管理的重要性,为数据资产管理体系建设提供系统性指导。【方法】通过阐述ISO 55013在资产数据管理、资产数据价值、识别数据资产、管理数据资产和数据治理等方面的核心要素,结合资产管理体系实践,提出数据资产密集型组织在管理实践方面的有效路径。【结果】ISO 55013为组织提供了数据资产管理指南,推动组织应用ISO 55001给出的资产管理体系管理数据。【结论】ISO 55013将为数据资产管理体系建设的规范化提供依据,推动组织在数字经济时代在数据资产管理中充分获取价值。展开更多
The problems associated with vibrations of viaducts and low-frequency structural noise radiation caused by train excitation continue to increase in importance.A new floating-slab track vibration isolator-non-obstructi...The problems associated with vibrations of viaducts and low-frequency structural noise radiation caused by train excitation continue to increase in importance.A new floating-slab track vibration isolator-non-obstructive particle damping-phononic crystal vibration isolator is proposed herein,which uses the particle damping vibration absorption technology and bandgap vibration control theory.The vibration reduction performance of the NOPD-PCVI was analyzed from the perspective of vibration control.The paper explores the structure-borne noise reduction performance of the NOPD-PCVIs installed on different bridge structures under varying service conditions encountered in practical engineering applications.The load transferred to the bridge is obtained from a coupled train-FST-bridge analytical model considering the different structural parameters of bridges.The vibration responses are obtained using the finite element method,while the structural noise radiation is simulated using the frequency-domain boundary element method.Using the particle swarm optimization algorithm,the parameters of the NOPD-PCVI are optimized so that its frequency bandgap matches the dominant bridge structural noise frequency range.The noise reduction performance of the NOPD-PCVIs is compared to the steel-spring isolation under different service conditions.展开更多
This paper presents isogeometric analysis(IGA)-based topology optimization for electrical performance of three-dimensional(3D)flexoelectric structures.IGA is employed to provide{C}^{1}continuity in shape function,whic...This paper presents isogeometric analysis(IGA)-based topology optimization for electrical performance of three-dimensional(3D)flexoelectric structures.IGA is employed to provide{C}^{1}continuity in shape function,which is required in treating high-order electromechanical coupling equations.To improve the computational efficiency in treating 3D problems,the redundant degrees of freedom removal technique is introduced.Regularization treatments are also implemented to avoid the numerical singularity induced by flexoelectricity.Both virtual loads and strain energy constraints are taken into consideration to prevent unexpected structural disconnection.Numerical examples and experiments on optimized structures demonstrate that the flexoelectric performance can be effectively improved using the proposed approach.展开更多
The selection of important factors in machine learning-based susceptibility assessments is crucial to obtain reliable susceptibility results.In this study,metaheuristic optimization and feature selection techniques we...The selection of important factors in machine learning-based susceptibility assessments is crucial to obtain reliable susceptibility results.In this study,metaheuristic optimization and feature selection techniques were applied to identify the most important input parameters for mapping debris flow susceptibility in the southern mountain area of Chengde City in Hebei Province,China,by using machine learning algorithms.In total,133 historical debris flow records and 16 related factors were selected.The support vector machine(SVM)was first used as the base classifier,and then a hybrid model was introduced by a two-step process.First,the particle swarm optimization(PSO)algorithm was employed to select the SVM model hyperparameters.Second,two feature selection algorithms,namely principal component analysis(PCA)and PSO,were integrated into the PSO-based SVM model,which generated the PCA-PSO-SVM and FS-PSO-SVM models,respectively.Three statistical metrics(accuracy,recall,and specificity)and the area under the receiver operating characteristic curve(AUC)were employed to evaluate and validate the performance of the models.The results indicated that the feature selection-based models exhibited the best performance,followed by the PSO-based SVM and SVM models.Moreover,the performance of the FS-PSO-SVM model was better than that of the PCA-PSO-SVM model,showing the highest AUC,accuracy,recall,and specificity values in both the training and testing processes.It was found that the selection of optimal features is crucial to improving the reliability of debris flow susceptibility assessment results.Moreover,the PSO algorithm was found to be not only an effective tool for hyperparameter optimization,but also a useful feature selection algorithm to improve prediction accuracies of debris flow susceptibility by using machine learning algorithms.The high and very high debris flow susceptibility zone appropriately covers 38.01%of the study area,where debris flow may occur under intensive human activities and heavy rainfall events.展开更多
文摘This study investigates the potential of Prosopis cineraria Leaves Powder(PCLP)as a biosorbent for removing lead(Pb)and zinc(Zn)from aqueous solutions,optimizing the process using Response Surface Methodology(RSM).Prosopis cineraria,commonly known as Khejri,is a drought-resistant tree with significant promise in environmental applications.The research employed a Central Composite Design(CCD)to examine the independent and combined effects of key process variables,including initial metal ion concentration,contact time,pH,and PCLP dosage.RSM was used to develop mathematical models that explain the relationship between these factors and the efficiency of metal removal,allowing the determination of optimal operating conditions.The experimental results indicated that the Langmuir isotherm model was the most appropriate for describing the biosorption of both metals,suggesting favorable adsorption characteristics.Additionally,the D-R isotherm confirmed that chemisorption was the primary mechanism involved in the biosorption process.For lead removal,the optimal conditions were found to be 312.23 K temperature,pH 4.72,58.5 mg L-1 initial concentration,and 0.27 g biosorbent dosage,achieving an 83.77%removal efficiency.For zinc,the optimal conditions were 312.4 K,pH 5.86,53.07 mg L-1 initial concentration,and the same biosorbent dosage,resulting in a 75.86%removal efficiency.These findings highlight PCLP’s potential as an effective,eco-friendly biosorbent for sustainable heavy metal removal in water treatment.
基金supported by the Natural Science Foundation of China(Nos.22277019,82150204,22307031,22377023,22077143,and 82003594)Key Project of Guangdong Natural Science Foundation(No.2016A030311033)+2 种基金Fundamental Research Funds for Hainan University(Nos.KYQD(ZR)-21031,KYQD(ZR)-21108,KYQD(ZR)-23003,and XTCX2022JKA01)Guangdong Provincial Key Laboratory of Construction Foundation(No.2023B1212060022)Science Foundation of Hainan Province(Nos.KJRC2023B10,824YXQN420,and 324MS018)。
文摘Idiopathic pulmonary fibrosis(IPF)is a progressive lung disease and its incidence rate is rapidly rising.However,effective therapies for the treatment of IPF are still lacking.Phosphodiesterase 4(PDE4)inhibitors were reported to be potential anti-fibrotic agents.Herein,structure-based hit-to-lead optimization of natural isoaurostatin(8.98μmol/L)resulted in several potent inhibitors of PDE4 with half maximal inhibitory concentration(IC_(50))values ranging from 35 nmol/L to 126 nmol/L.Co-crystal structures revealed that isoaurostatin compounds exhibited different binding patterns from the classic PDE4 inhibitor rolipram and the analogues would favor to be Z configurations other than the corresponding E isomers.Finally,lead 2–9 showed remarkable in vitro/in vivo anti-fibrotic effects indicating its potential as a novel anti-IPF agent.
基金supported by the National Key R&D Program of China(2023YFB2504601)National Natural Science Foundation of China(52205267).
文摘Due to the high-order B-spline basis functions utilized in isogeometric analysis(IGA)and the repeatedly updating global stiffness matrix of topology optimization,Isogeometric topology optimization(ITO)intrinsically suffers from the computationally demanding process.In this work,we address the efficiency problem existing in the assembling stiffness matrix and sensitivity analysis using B˙ezier element stiffness mapping.The Element-wise and Interaction-wise parallel computing frameworks for updating the global stiffness matrix are proposed for ITO with B˙ezier element stiffness mapping,which differs from these ones with the traditional Gaussian integrals utilized.Since the explicit stiffness computation formula derived from B˙ezier element stiffness mapping possesses a typical parallel structure,the presented GPU-enabled ITO method can greatly accelerate the computation speed while maintaining its high memory efficiency unaltered.Numerical examples demonstrate threefold speedup:1)the assembling stiffness matrix is accelerated by 10×maximumly with the proposed GPU strategy;2)the solution efficiency of a sparse linear system is enhanced by up to 30×with Eigen replaced by AMGCL;3)the efficiency of sensitivity analysis is promoted by 100×with GPU applied.Therefore,the proposed method is a promising way to enhance the numerical efficiency of ITO for both single-patch and multiple-patch design problems.
基金supported by the National Natural Science Founda-tion of China under Grant Nos.42472351,42177140,52404127,and 42207235the Natural Science Foundation of Hubei Province under Grant No.2024AFD359+1 种基金the Young Elite Scientist Sponsorship Program by CAST under Grant No.YESS20230742the China Postdoctoral Science Foundation Program under Grant No.2024T170684.
文摘Rockburst is a common dynamic geological hazard,frequently occurring in underground engineering(e.g.,TBM tunnelling and deep mining).In order to achieve rockburst monitoring and warning,the microseismic moni-toring technique has been widely used in the field.However,the microseismic source location has always been a challenge,playing a vital role in the precise prevention and control of rockburst.To this end,this study proposes a novel microseismic source location model that considers the anisotropy of P-wave velocity.On the one hand,it assigns a unique P-wave velocity to each propagation path,abandoning the assumption of a homogeneous ve-locity field.On the other hand,it treats the P-wave velocity as a co-inversion parameter along with the source location,avoiding the predetermination of P-wave velocity.To solve this model,three various metaheuristic multi-objective optimization algorithms are integrated with it,including the whale optimization algorithm,the butterfly optimization algorithm,and the sparrow search algorithm.To demonstrate the advantages of the model in terms of localization accuracy,localization efficiency,and solution stability,four blasting cases are collected from a water diversion tunnel project in Xinjiang,China.Finally,the effect of the number of involved sensors on the microseismic source location is discussed.
文摘【目的】分析了ISO 55013:2024 Asset management—Guidance on the management of data assets国际标准的主要内容,该标准阐释了将数据视为资产予以有效管理的重要性,为数据资产管理体系建设提供系统性指导。【方法】通过阐述ISO 55013在资产数据管理、资产数据价值、识别数据资产、管理数据资产和数据治理等方面的核心要素,结合资产管理体系实践,提出数据资产密集型组织在管理实践方面的有效路径。【结果】ISO 55013为组织提供了数据资产管理指南,推动组织应用ISO 55001给出的资产管理体系管理数据。【结论】ISO 55013将为数据资产管理体系建设的规范化提供依据,推动组织在数字经济时代在数据资产管理中充分获取价值。
基金Project(51978585)supported by the National Natural Science Foundation,ChinaProject(2022YFB2603404)supported by the National Key Research and Development Program,China+1 种基金Project(U1734207)supported by the High-speed Rail Joint Fund Key Projects of Basic Research,ChinaProject(2023NSFSC1975)supported by the Sichuan Nature and Science Foundation Innovation Research Group Project,China。
文摘The problems associated with vibrations of viaducts and low-frequency structural noise radiation caused by train excitation continue to increase in importance.A new floating-slab track vibration isolator-non-obstructive particle damping-phononic crystal vibration isolator is proposed herein,which uses the particle damping vibration absorption technology and bandgap vibration control theory.The vibration reduction performance of the NOPD-PCVI was analyzed from the perspective of vibration control.The paper explores the structure-borne noise reduction performance of the NOPD-PCVIs installed on different bridge structures under varying service conditions encountered in practical engineering applications.The load transferred to the bridge is obtained from a coupled train-FST-bridge analytical model considering the different structural parameters of bridges.The vibration responses are obtained using the finite element method,while the structural noise radiation is simulated using the frequency-domain boundary element method.Using the particle swarm optimization algorithm,the parameters of the NOPD-PCVI are optimized so that its frequency bandgap matches the dominant bridge structural noise frequency range.The noise reduction performance of the NOPD-PCVIs is compared to the steel-spring isolation under different service conditions.
基金support from the National Natural Science Foundation of China(12272075)Liao Ning Revitalization Talents Program(XLYC2001003,XLYC1907119)+1 种基金Fundamental Research Funds for the Central Universities(DUT22QN238)Program for Changjiang Scholars,Innovative Research Team in University(PCSIRT)and 111 Project(B14013)is gratefully acknowledged.
文摘This paper presents isogeometric analysis(IGA)-based topology optimization for electrical performance of three-dimensional(3D)flexoelectric structures.IGA is employed to provide{C}^{1}continuity in shape function,which is required in treating high-order electromechanical coupling equations.To improve the computational efficiency in treating 3D problems,the redundant degrees of freedom removal technique is introduced.Regularization treatments are also implemented to avoid the numerical singularity induced by flexoelectricity.Both virtual loads and strain energy constraints are taken into consideration to prevent unexpected structural disconnection.Numerical examples and experiments on optimized structures demonstrate that the flexoelectric performance can be effectively improved using the proposed approach.
基金supported by the Second Tibetan Plateau Scientific Expedition and Research Program(Grant no.2019QZKK0904)Natural Science Foundation of Hebei Province(Grant no.D2022403032)S&T Program of Hebei(Grant no.E2021403001).
文摘The selection of important factors in machine learning-based susceptibility assessments is crucial to obtain reliable susceptibility results.In this study,metaheuristic optimization and feature selection techniques were applied to identify the most important input parameters for mapping debris flow susceptibility in the southern mountain area of Chengde City in Hebei Province,China,by using machine learning algorithms.In total,133 historical debris flow records and 16 related factors were selected.The support vector machine(SVM)was first used as the base classifier,and then a hybrid model was introduced by a two-step process.First,the particle swarm optimization(PSO)algorithm was employed to select the SVM model hyperparameters.Second,two feature selection algorithms,namely principal component analysis(PCA)and PSO,were integrated into the PSO-based SVM model,which generated the PCA-PSO-SVM and FS-PSO-SVM models,respectively.Three statistical metrics(accuracy,recall,and specificity)and the area under the receiver operating characteristic curve(AUC)were employed to evaluate and validate the performance of the models.The results indicated that the feature selection-based models exhibited the best performance,followed by the PSO-based SVM and SVM models.Moreover,the performance of the FS-PSO-SVM model was better than that of the PCA-PSO-SVM model,showing the highest AUC,accuracy,recall,and specificity values in both the training and testing processes.It was found that the selection of optimal features is crucial to improving the reliability of debris flow susceptibility assessment results.Moreover,the PSO algorithm was found to be not only an effective tool for hyperparameter optimization,but also a useful feature selection algorithm to improve prediction accuracies of debris flow susceptibility by using machine learning algorithms.The high and very high debris flow susceptibility zone appropriately covers 38.01%of the study area,where debris flow may occur under intensive human activities and heavy rainfall events.
