Structure evaluation is critical to in silico 3-dimensional structure predictions for biomacromolecules such as proteins and RNAs.For proteins,structure evaluation has been paid attention over three decades along with...Structure evaluation is critical to in silico 3-dimensional structure predictions for biomacromolecules such as proteins and RNAs.For proteins,structure evaluation has been paid attention over three decades along with protein folding problem,and statistical potentials have been shown to be effective and efficient in protein structure prediction and evaluation.In recent two decades,RNA folding problem has attracted much attention and several statistical potentials have been developed for RNA structure evaluation,partially with the aid of the progress in protein structure prediction.In this review,we will firstly give a brief overview on the existing statistical potentials for protein structure evaluation.Afterwards,we will introduce the recently developed statistical potentials for RNA structure evaluation.Finally,we will emphasize the perspective on developing new statistical potentials for RNAs in the near future.展开更多
Knowledge of RNA 3-dimensional(3 D) structures is critical to understand the important biological functions of RNAs, and various models have been developed to predict RNA 3 D structures in silico. However, there is st...Knowledge of RNA 3-dimensional(3 D) structures is critical to understand the important biological functions of RNAs, and various models have been developed to predict RNA 3 D structures in silico. However, there is still lack of a reliable and efficient statistical potential for RNA 3 D structure evaluation. For this purpose, we developed a statistical potential based on a minimal coarse-grained representation and residue separation, where every nucleotide is represented by C4’ atom for backbone and N1(or N9) atom for base. In analogy to the newly developed all-atom rsRNASP, cgRNASP-CN is composed of short-ranged and long-ranged potentials, and the short-ranged one was involved more subtly. The examination indicates that the performance of cgRNASP-CN is close to that of the all-atom rsRNASP and is superior to other top all-atom traditional statistical potentials and scoring functions trained from neural networks, for two realistic test datasets including the RNA-Puzzles dataset. Very importantly,cgRNASP-CN is about 100 times more efficient than existing all-atom statistical potentials/scoring functions including rsRNASP. cgRNASP-CN is available at website: https://github.com/Tan-group/cgRNASP-CN.展开更多
By using the concept of modified structural number(SNC)and deflection measurements,a simplified calculation methodology,that permits the structural condition evaluation of an existing pavement,is being proposed.The va...By using the concept of modified structural number(SNC)and deflection measurements,a simplified calculation methodology,that permits the structural condition evaluation of an existing pavement,is being proposed.The values of SNC and the curvature parameters were first determined through simulations using the ELSYM-5 software.Deflection measurements were carried out in experimental segments of Brazilian highways.The resilient moduli of each layer were determined from backcalculation using the ELMOD program for a three-layer system.Theoretical correlation models between SNC and the basin deformation parameter were determined and later,calibrated with the results of experimental sections.Utilizing the studied models,a good correlation was found between SNC,area parameter and maximum deflection,enabling the determination of SNC through deflection measurements and assisting in the diagnostic of structural condition of asphalt pavements.展开更多
The present study is endeavored to study the oxidative stress and antioxidant response as well as the ultrastructural change of both liver and muscle tissues of Siganus rivulatus collected from polluted region (El-Mex...The present study is endeavored to study the oxidative stress and antioxidant response as well as the ultrastructural change of both liver and muscle tissues of Siganus rivulatus collected from polluted region (El-Mex Bay) and control region (Marsa Matrouh) to identify the significance of biomarkers. The results revealed that, El-Mex Bay was polluted by different types of chemicals including hydrocarbons comparing with the reference area (Matrouh area). Where, the concentration range of total hydrocarbons in sediment samples collected from Matrouh coast was 409.24 - 521.26 ng/g, dry weight, where as this range in sediment samples collected from El-MexBay was 4159.77 - 4589.81 ng/g, dry weight. In this context, the induction of antioxidant systems in fish collected from polluted area in response to oxidative stress should be considered as a clear indication of the presence of pollution and environmental health degradation. Also, The increase in lipid peroxidation was a useful indicator of the pollution load in the present study. The results suggest that chemical pollution is capable of inducing morphological alteration in liver offish collected from polluted area. The present study indicated that ultra-structural changes serveas biomarker of stress in aquatic environment.展开更多
The construction of relevant standards for building carbon emission assessment in China has just started,and the quantitative analysis method and evaluation system are still imperfect,which hinders the development of ...The construction of relevant standards for building carbon emission assessment in China has just started,and the quantitative analysis method and evaluation system are still imperfect,which hinders the development of low-carbon building design.Therefore,the use of intelligent energy management system is very necessary.The purpose of this paper is to explore the design optimization of low-carbon buildings based on intelligent energy management systems.Based on the proposed quantitative method of building carbon emission,this paper establishes the quota theoretical system of building carbon emission analysis,and develops the quota based carbon emission calculation software.Smart energy management system is a low-carbon energy-saving system based on the reference of large-scale building energy-saving system and combined with energy consumption.It provides a fast and effective calculation tool for the quantitative evaluation of carbon emission of construction projects,so as to realize the carbon emission control and optimization in the early stage of architectural design and construction.On this basis,the evaluation,analysis and calculation method of building structure based on carbon reduction target is proposed,combined with the carbon emission quota management standard proposed in this paper.Taking small high-rise residential buildings as an example,this paper compares and analyzes different building structural systems from the perspectives of structural performance,economy and carbon emission level.It provides a reference for the design and evaluation of low-carbon building structures.The smart energy management system collects user energy use parameters.It uses time period and time sequence to obtain a large amount of data for analysis and integration,which provides users with intuitive energy consumption data.Compared with the traditional architectural design method,the industrialized construction method can save 589.22 megajoules(MJ)per square meter.Based on 29270 megajoules(MJ)per ton of standard coal,the construction area of the case is about 8000 m2,and the energy saving of residential buildings is 161.04 tons of standard coal.This research is of great significance in reducing the carbon emission intensity of buildings.展开更多
This paper presents an electrical impedance tomography(EIT)method using a partial-differential-equationconstrained optimization approach.The forward problem in the inversion framework is described by a complete electr...This paper presents an electrical impedance tomography(EIT)method using a partial-differential-equationconstrained optimization approach.The forward problem in the inversion framework is described by a complete electrodemodel(CEM),which seeks the electric potential within the domain and at surface electrodes considering the contact impedance between them.The finite element solution of the electric potential has been validated using a commercial code.The inverse medium problem for reconstructing the unknown electrical conductivity profile is formulated as an optimization problem constrained by the CEM.The method seeks the optimal solution of the domain’s electrical conductivity to minimize a Lagrangian functional consisting of a least-squares objective functional and a regularization term.Enforcing the stationarity of the Lagrangian leads to state,adjoint,and control problems,which constitute the Karush-Kuhn-Tucker(KKT)first-order optimality conditions.Subsequently,the electrical conductivity profile of the domain is iteratively updated by solving the KKT conditions in the reduced space of the control variable.Numerical results show that the relative error of the measured and calculated electric potentials after the inversion is less than 1%,demonstrating the successful reconstruction of heterogeneous electrical conductivity profiles using the proposed EIT method.This method thus represents an application framework for nondestructive evaluation of structures and geotechnical site characterization.展开更多
To make the quantitative results of nuclear magnetic resonance(NMR) transverse relaxation(T;) spectrums reflect the type and pore structure of reservoir more directly, an unsupervised clustering method was developed t...To make the quantitative results of nuclear magnetic resonance(NMR) transverse relaxation(T;) spectrums reflect the type and pore structure of reservoir more directly, an unsupervised clustering method was developed to obtain the quantitative pore structure information from the NMR T;spectrums based on the Gaussian mixture model(GMM). Firstly, We conducted the principal component analysis on T;spectrums in order to reduce the dimension data and the dependence of the original variables. Secondly, the dimension-reduced data was fitted using the GMM probability density function, and the model parameters and optimal clustering numbers were obtained according to the expectation-maximization algorithm and the change of the Akaike information criterion. Finally, the T;spectrum features and pore structure types of different clustering groups were analyzed and compared with T;geometric mean and T;arithmetic mean. The effectiveness of the algorithm has been verified by numerical simulation and field NMR logging data. The research shows that the clustering results based on GMM method have good correlations with the shape and distribution of the T;spectrum, pore structure, and petroleum productivity, providing a new means for quantitative identification of pore structure, reservoir grading, and oil and gas productivity evaluation.展开更多
The great diversity of dedicated hybrid transmissions(DHTs)requires a method to identify solutions among all potential concepts involved in each structure.Therefore,a DHT synthesis tool is developed on the basis of ge...The great diversity of dedicated hybrid transmissions(DHTs)requires a method to identify solutions among all potential concepts involved in each structure.Therefore,a DHT synthesis tool is developed on the basis of general transmission synthesis.In the first synthesis step,transmission structures are generated with only conventional functions such as driving with only the internal combustion engine.Electric machines are then installed in the transmissions to achieve further hybrid functions,including boosting,eCVT and electric driving modes.The number of generated transmission concepts increases exponentially with each synthesis step.Various evaluations are carried out successively to identify the most suitable DHT concepts among the many possible solutions.The generated DHT concepts are evaluated in terms of structural feasibility,driving modes,drivability and load factors on transmission components.An example of DHT synthesis involving planetary gear sets is explained in detail.The best five DHT structures are identified out of more than 120 billion solutions.展开更多
基金Project supported by the National Natural Science Foundation of China(Grant Nos.11774272 and 11575128)。
文摘Structure evaluation is critical to in silico 3-dimensional structure predictions for biomacromolecules such as proteins and RNAs.For proteins,structure evaluation has been paid attention over three decades along with protein folding problem,and statistical potentials have been shown to be effective and efficient in protein structure prediction and evaluation.In recent two decades,RNA folding problem has attracted much attention and several statistical potentials have been developed for RNA structure evaluation,partially with the aid of the progress in protein structure prediction.In this review,we will firstly give a brief overview on the existing statistical potentials for protein structure evaluation.Afterwards,we will introduce the recently developed statistical potentials for RNA structure evaluation.Finally,we will emphasize the perspective on developing new statistical potentials for RNAs in the near future.
基金supported by grants from the National Science Foundation of China(12075171,11774272)。
文摘Knowledge of RNA 3-dimensional(3 D) structures is critical to understand the important biological functions of RNAs, and various models have been developed to predict RNA 3 D structures in silico. However, there is still lack of a reliable and efficient statistical potential for RNA 3 D structure evaluation. For this purpose, we developed a statistical potential based on a minimal coarse-grained representation and residue separation, where every nucleotide is represented by C4’ atom for backbone and N1(or N9) atom for base. In analogy to the newly developed all-atom rsRNASP, cgRNASP-CN is composed of short-ranged and long-ranged potentials, and the short-ranged one was involved more subtly. The examination indicates that the performance of cgRNASP-CN is close to that of the all-atom rsRNASP and is superior to other top all-atom traditional statistical potentials and scoring functions trained from neural networks, for two realistic test datasets including the RNA-Puzzles dataset. Very importantly,cgRNASP-CN is about 100 times more efficient than existing all-atom statistical potentials/scoring functions including rsRNASP. cgRNASP-CN is available at website: https://github.com/Tan-group/cgRNASP-CN.
文摘By using the concept of modified structural number(SNC)and deflection measurements,a simplified calculation methodology,that permits the structural condition evaluation of an existing pavement,is being proposed.The values of SNC and the curvature parameters were first determined through simulations using the ELSYM-5 software.Deflection measurements were carried out in experimental segments of Brazilian highways.The resilient moduli of each layer were determined from backcalculation using the ELMOD program for a three-layer system.Theoretical correlation models between SNC and the basin deformation parameter were determined and later,calibrated with the results of experimental sections.Utilizing the studied models,a good correlation was found between SNC,area parameter and maximum deflection,enabling the determination of SNC through deflection measurements and assisting in the diagnostic of structural condition of asphalt pavements.
文摘The present study is endeavored to study the oxidative stress and antioxidant response as well as the ultrastructural change of both liver and muscle tissues of Siganus rivulatus collected from polluted region (El-Mex Bay) and control region (Marsa Matrouh) to identify the significance of biomarkers. The results revealed that, El-Mex Bay was polluted by different types of chemicals including hydrocarbons comparing with the reference area (Matrouh area). Where, the concentration range of total hydrocarbons in sediment samples collected from Matrouh coast was 409.24 - 521.26 ng/g, dry weight, where as this range in sediment samples collected from El-MexBay was 4159.77 - 4589.81 ng/g, dry weight. In this context, the induction of antioxidant systems in fish collected from polluted area in response to oxidative stress should be considered as a clear indication of the presence of pollution and environmental health degradation. Also, The increase in lipid peroxidation was a useful indicator of the pollution load in the present study. The results suggest that chemical pollution is capable of inducing morphological alteration in liver offish collected from polluted area. The present study indicated that ultra-structural changes serveas biomarker of stress in aquatic environment.
基金supported by“Key Technology Research on Operational Performance Improvement of the Green Building”(2020YFS0060)Key Project of Science and Technology Department of Sichuan Province+2 种基金supported by“Creative VR Teaching and Learning Research Based on‘PBL+’and Multidimensional Collaboration”(JG2021-721)“Reform in the Mode and Practice of Architecture Education with the Characteristics of Geology”(JG2021-672)Education Quality and Teaching Reform Project of Higher Education in Sichuan Province in 2021–2023.
文摘The construction of relevant standards for building carbon emission assessment in China has just started,and the quantitative analysis method and evaluation system are still imperfect,which hinders the development of low-carbon building design.Therefore,the use of intelligent energy management system is very necessary.The purpose of this paper is to explore the design optimization of low-carbon buildings based on intelligent energy management systems.Based on the proposed quantitative method of building carbon emission,this paper establishes the quota theoretical system of building carbon emission analysis,and develops the quota based carbon emission calculation software.Smart energy management system is a low-carbon energy-saving system based on the reference of large-scale building energy-saving system and combined with energy consumption.It provides a fast and effective calculation tool for the quantitative evaluation of carbon emission of construction projects,so as to realize the carbon emission control and optimization in the early stage of architectural design and construction.On this basis,the evaluation,analysis and calculation method of building structure based on carbon reduction target is proposed,combined with the carbon emission quota management standard proposed in this paper.Taking small high-rise residential buildings as an example,this paper compares and analyzes different building structural systems from the perspectives of structural performance,economy and carbon emission level.It provides a reference for the design and evaluation of low-carbon building structures.The smart energy management system collects user energy use parameters.It uses time period and time sequence to obtain a large amount of data for analysis and integration,which provides users with intuitive energy consumption data.Compared with the traditional architectural design method,the industrialized construction method can save 589.22 megajoules(MJ)per square meter.Based on 29270 megajoules(MJ)per ton of standard coal,the construction area of the case is about 8000 m2,and the energy saving of residential buildings is 161.04 tons of standard coal.This research is of great significance in reducing the carbon emission intensity of buildings.
基金funded by the National Research Foundation of Korea,the Grant from a Basic Science and Engineering Research Project(NRF-2017R1C1B200497515)and the Grant from Basic Laboratory Support Project(NRF-2020R1A4A101882611).
文摘This paper presents an electrical impedance tomography(EIT)method using a partial-differential-equationconstrained optimization approach.The forward problem in the inversion framework is described by a complete electrodemodel(CEM),which seeks the electric potential within the domain and at surface electrodes considering the contact impedance between them.The finite element solution of the electric potential has been validated using a commercial code.The inverse medium problem for reconstructing the unknown electrical conductivity profile is formulated as an optimization problem constrained by the CEM.The method seeks the optimal solution of the domain’s electrical conductivity to minimize a Lagrangian functional consisting of a least-squares objective functional and a regularization term.Enforcing the stationarity of the Lagrangian leads to state,adjoint,and control problems,which constitute the Karush-Kuhn-Tucker(KKT)first-order optimality conditions.Subsequently,the electrical conductivity profile of the domain is iteratively updated by solving the KKT conditions in the reduced space of the control variable.Numerical results show that the relative error of the measured and calculated electric potentials after the inversion is less than 1%,demonstrating the successful reconstruction of heterogeneous electrical conductivity profiles using the proposed EIT method.This method thus represents an application framework for nondestructive evaluation of structures and geotechnical site characterization.
基金Supported by the National Natural Science Foundation of China (42174142)National Science and Technology Major Project (2017ZX05039-002)+2 种基金Operation Fund of China National Petroleum Corporation Logging Key Laboratory (2021DQ20210107-11)Fundamental Research Funds for Central Universities (19CX02006A)Major Science and Technology Project of China National Petroleum Corporation (ZD2019-183-006)。
文摘To make the quantitative results of nuclear magnetic resonance(NMR) transverse relaxation(T;) spectrums reflect the type and pore structure of reservoir more directly, an unsupervised clustering method was developed to obtain the quantitative pore structure information from the NMR T;spectrums based on the Gaussian mixture model(GMM). Firstly, We conducted the principal component analysis on T;spectrums in order to reduce the dimension data and the dependence of the original variables. Secondly, the dimension-reduced data was fitted using the GMM probability density function, and the model parameters and optimal clustering numbers were obtained according to the expectation-maximization algorithm and the change of the Akaike information criterion. Finally, the T;spectrum features and pore structure types of different clustering groups were analyzed and compared with T;geometric mean and T;arithmetic mean. The effectiveness of the algorithm has been verified by numerical simulation and field NMR logging data. The research shows that the clustering results based on GMM method have good correlations with the shape and distribution of the T;spectrum, pore structure, and petroleum productivity, providing a new means for quantitative identification of pore structure, reservoir grading, and oil and gas productivity evaluation.
文摘The great diversity of dedicated hybrid transmissions(DHTs)requires a method to identify solutions among all potential concepts involved in each structure.Therefore,a DHT synthesis tool is developed on the basis of general transmission synthesis.In the first synthesis step,transmission structures are generated with only conventional functions such as driving with only the internal combustion engine.Electric machines are then installed in the transmissions to achieve further hybrid functions,including boosting,eCVT and electric driving modes.The number of generated transmission concepts increases exponentially with each synthesis step.Various evaluations are carried out successively to identify the most suitable DHT concepts among the many possible solutions.The generated DHT concepts are evaluated in terms of structural feasibility,driving modes,drivability and load factors on transmission components.An example of DHT synthesis involving planetary gear sets is explained in detail.The best five DHT structures are identified out of more than 120 billion solutions.
