To predict the wave loads of a flexible trimaran in different wave fields,a one-way interaction numerical simulation method is proposed by integrating the fluid solver(Star-CCM+)and structural solver(Abaqus).Differing...To predict the wave loads of a flexible trimaran in different wave fields,a one-way interaction numerical simulation method is proposed by integrating the fluid solver(Star-CCM+)and structural solver(Abaqus).Differing from the existing coupled CFD-FEA method for monohull ships in head waves,the presented method equates the mass and stiffness of the whole ship to the hull shell so that any transverse and longitudinal section stress of the hull in oblique waves can be obtained.Firstly,verification study and sensitivity analysis are carried out by comparing the trimaran motions using different mesh sizes and time step schemes.Discussion on the wave elevation of uni-and bi-directional waves is also carried out.Then a comprehensive analysis on the structural responses of the trimaran in different uni-directional regular wave and bi-directional cross sea conditions is carried out,respectively.Finally,the differences in structural response characteristics of trimaran in different wave fields are studied.The results show that the present method can reduce the computational burden of the two-way fluid-structure interaction simulations.展开更多
Security during remote transmission has been an important concern for researchers in recent years.In this paper,a hierarchical encryption multi-image encryption scheme for people with different security levels is desi...Security during remote transmission has been an important concern for researchers in recent years.In this paper,a hierarchical encryption multi-image encryption scheme for people with different security levels is designed,and a multiimage encryption(MIE)algorithm with row and column confusion and closed-loop bi-directional diffusion is adopted in the paper.While ensuring secure communication of medical image information,people with different security levels have different levels of decryption keys,and differentiated visual effects can be obtained by using the strong sensitivity of chaotic keys.The highest security level can obtain decrypted images without watermarks,and at the same time,patient information and copyright attribution can be verified by obtaining watermark images.The experimental results show that the scheme is sufficiently secure as an MIE scheme with visualized differences and the encryption and decryption efficiency is significantly improved compared to other works.展开更多
Sentiment analysis,commonly called opinion mining or emotion artificial intelligence(AI),employs biometrics,computational linguistics,nat-ural language processing,and text analysis to systematically identify,extract,m...Sentiment analysis,commonly called opinion mining or emotion artificial intelligence(AI),employs biometrics,computational linguistics,nat-ural language processing,and text analysis to systematically identify,extract,measure,and investigate affective states and subjective data.Sentiment analy-sis algorithms include emotion lexicon,traditional machine learning,and deep learning.In the text sentiment analysis algorithm based on a neural network,multi-layer Bi-directional long short-term memory(LSTM)is widely used,but the parameter amount of this model is too huge.Hence,this paper proposes a Bi-directional LSTM with a trapezoidal structure model.The design of the trapezoidal structure is derived from classic neural networks,such as LeNet-5 and AlexNet.These classic models have trapezoidal-like structures,and these structures have achieved success in the field of deep learning.There are two benefits to using the Bi-directional LSTM with a trapezoidal structure.One is that compared with the single-layer configuration,using the of the multi-layer structure can better extract the high-dimensional features of the text.Another is that using the trapezoidal structure can reduce the model’s parameters.This paper introduces the Bi-directional LSTM with a trapezoidal structure model in detail and uses Stanford sentiment treebank 2(STS-2)for experiments.It can be seen from the experimental results that the trapezoidal structure model and the normal structure model have similar performances.However,the trapezoidal structure model parameters are 35.75%less than the normal structure model.展开更多
Natural frequency and dynamic stiffness under transient loading are two key performances for structural design related to automotive,aviation and construction industries.This article aims to tackle the multi-objective...Natural frequency and dynamic stiffness under transient loading are two key performances for structural design related to automotive,aviation and construction industries.This article aims to tackle the multi-objective topological optimization problem considering dynamic stiffness and natural frequency using modified version of bi-directional evolutionary structural optimization(BESO).The conventional BESO is provided with constant evolutionary volume ratio(EVR),whereas low EVR greatly retards the optimization process and high EVR improperly removes the efficient elements.To address the issue,the modified BESO with variable EVR is introduced.To compromise the natural frequency and the dynamic stiffness,a weighting scheme of sensitivity numbers is employed to form the Pareto solution space.Several numerical examples demonstrate that the optimal solutions obtained from the modified BESO method have good agreement with those from the classic BESO method.Most importantly,the dynamic removal strategy with the variable EVR sharply springs up the optimization process.Therefore,it is concluded that the modified BESO method with variable EVR can solve structural design problems using multi-objective optimization.展开更多
This study examines the wave propagation characteristics for a bi-directional functional grading of barium titanate(BaTiO_(3)) and cobalt ferrite(CoFe_(2)O_(4)) porous nanoshells,the porosity distribution of which is ...This study examines the wave propagation characteristics for a bi-directional functional grading of barium titanate(BaTiO_(3)) and cobalt ferrite(CoFe_(2)O_(4)) porous nanoshells,the porosity distribution of which is simulated by the honeycomb-shaped symmetrical and asymmetrical distribution functions.The nonlocal strain gradient theory(NSGT) and first-order shear deformation theory are used to determine the size effect and shear deformation,respectively.Nonlocal governing equations are derived for the nanoshells by Hamilton's principle.The resulting dimensionless differential equations are solved by means of an analytical solution of the combined exponential function after dimensionless treatment.Finally,extensive parametric surveys are conducted to investigate the influence of diverse parameters,such as dimensionless scale parameters,radiusto-thickness ratios,bi-directional functionally graded(FG) indices,porosity coefficients,and dimensionless electromagnetic potentials on the wave propagation characteristics.Based on the analysis results,the effect of the dimensionless scale parameters on the dispersion relationship is found to be related to the ratio of the scale parameters.The wave propagation characteristics of nanoshells in the presence of a magnetoelectric field depend on the bi-directional FG indices.展开更多
Skin cancer diagnosis is difficult due to lesion presentation variability. Conventionalmethods struggle to manuallyextract features and capture lesions spatial and temporal variations. This study introduces a deep lea...Skin cancer diagnosis is difficult due to lesion presentation variability. Conventionalmethods struggle to manuallyextract features and capture lesions spatial and temporal variations. This study introduces a deep learning-basedConvolutional and Recurrent Neural Network (CNN-RNN) model with a ResNet-50 architecture which usedas the feature extractor to enhance skin cancer classification. Leveraging synergistic spatial feature extractionand temporal sequence learning, the model demonstrates robust performance on a dataset of 9000 skin lesionphotos from nine cancer types. Using pre-trained ResNet-50 for spatial data extraction and Long Short-TermMemory (LSTM) for temporal dependencies, the model achieves a high average recognition accuracy, surpassingprevious methods. The comprehensive evaluation, including accuracy, precision, recall, and F1-score, underscoresthe model’s competence in categorizing skin cancer types. This research contributes a sophisticated model andvaluable guidance for deep learning-based diagnostics, also this model excels in overcoming spatial and temporalcomplexities, offering a sophisticated solution for dermatological diagnostics research.展开更多
Tunnel boring machines(TBMs)have been widely utilised in tunnel construction due to their high efficiency and reliability.Accurately predicting TBM performance can improve project time management,cost control,and risk...Tunnel boring machines(TBMs)have been widely utilised in tunnel construction due to their high efficiency and reliability.Accurately predicting TBM performance can improve project time management,cost control,and risk management.This study aims to use deep learning to develop real-time models for predicting the penetration rate(PR).The models are built using data from the Changsha metro project,and their performances are evaluated using unseen data from the Zhengzhou Metro project.In one-step forecast,the predicted penetration rate follows the trend of the measured penetration rate in both training and testing.The autoregressive integrated moving average(ARIMA)model is compared with the recurrent neural network(RNN)model.The results show that univariate models,which only consider historical penetration rate itself,perform better than multivariate models that take into account multiple geological and operational parameters(GEO and OP).Next,an RNN variant combining time series of penetration rate with the last-step geological and operational parameters is developed,and it performs better than other models.A sensitivity analysis shows that the penetration rate is the most important parameter,while other parameters have a smaller impact on time series forecasting.It is also found that smoothed data are easier to predict with high accuracy.Nevertheless,over-simplified data can lose real characteristics in time series.In conclusion,the RNN variant can accurately predict the next-step penetration rate,and data smoothing is crucial in time series forecasting.This study provides practical guidance for TBM performance forecasting in practical engineering.展开更多
The multi-agent system is the optimal solution to complex intelligent problems. In accordance with the game theory, the concept of loyalty is introduced to analyze the relationship between agents' individual incom...The multi-agent system is the optimal solution to complex intelligent problems. In accordance with the game theory, the concept of loyalty is introduced to analyze the relationship between agents' individual income and global benefits and build the logical architecture of the multi-agent system. Besides, to verify the feasibility of the method, the cyclic neural network is optimized, the bi-directional coordination network is built as the training network for deep learning, and specific training scenes are simulated as the training background. After a certain number of training iterations, the model can learn simple strategies autonomously. Also,as the training time increases, the complexity of learning strategies rises gradually. Strategies such as obstacle avoidance, firepower distribution and collaborative cover are adopted to demonstrate the achievability of the model. The model is verified to be realizable by the examples of obstacle avoidance, fire distribution and cooperative cover. Under the same resource background, the model exhibits better convergence than other deep learning training networks, and it is not easy to fall into the local endless loop.Furthermore, the ability of the learning strategy is stronger than that of the training model based on rules, which is of great practical values.展开更多
The local scour around a new pile-group foundation of offshore wind turbine subjected to a bi-directional current was physically modeled with a bi-directional flow flume. In a series of experiments, the flow velocity ...The local scour around a new pile-group foundation of offshore wind turbine subjected to a bi-directional current was physically modeled with a bi-directional flow flume. In a series of experiments, the flow velocity and topography of the seabed were measured based on a system composed of plane positioning equipment and an ADV.Experimental results indicate that the development of the scour hole was fast at the beginning, but then the scour rate decreased until reaching equilibrium. Erosion would occur around each pile of the foundation. In most cases, the scour pits were connected in pairs and the outside widths of the scour holes were larger than the inner widths. The maximum scour depth occurred at the side pile of the foundation for each test. In addition, a preliminary investigation shows that the larger the flow velocity, the larger the scour hole dimensions but the shorter equilibrium time. The field maximum scour depth around the foundation was obtained based on the physical experiments with the geometric length scales of 1:27.0, 1:42.5 and 1:68.0, and it agrees with the scour depth estimated by the HEC-18 equation.展开更多
The constitutive promoter of cauliflower mosaic virus 35S (CaMV 35S) is a polar unidirectional promoter and is widely used in plant genetic engineering. In the present study, the unidirectional CaMV 35S promoter has...The constitutive promoter of cauliflower mosaic virus 35S (CaMV 35S) is a polar unidirectional promoter and is widely used in plant genetic engineering. In the present study, the unidirectional CaMV 35S promoter has been modified to a bi-directional promoter by fusing its minimal promoter element to the 5' end of CaMV 35S promoter in the opposite orientation. To qualitatively and quantitatively estimate its bi-directional transcriptional function and activity, two visible reporter genes, gusA (13-glucuronidase, GUS) and gfp (green fluorescent protein, GFP), were fused to the two ends of the promoter in bi-orientations ending with NOS terminator sequences, respectively. Stable expression of gusA and gfp genes in transgenic tobacco (Nicotiana tabacum L.) was visulized by histochemically staining for GUS and fluorescence microscopic observation under UV for GFP in transgenic plants. The expression of two reporter genes showed that the constructed bi-directional promoter did have the bi-directional transcriptional function in both expected orientations. The quantitative estimation of GUS and GFP were determined on a HITACHI F1000 Fluorescence Spectrophotometer with various wavelengths of excitation and emission. The GUS activity varied from g to 250 pmol 4-MU/min/mg protein and the GFP content varied from 0.9 to 1.8 μg/ mg protein in various lines of transgenic tobacco plants. Higher GUS activity generally coupled with lower GFP content, and vice versa.展开更多
The one-dimensional (1D) spatial distributions of OH absolute concentration in methane/air laminar premixed flat flame under different equivalence ratios at atmospheric pressure are investigated by using bi-directio...The one-dimensional (1D) spatial distributions of OH absolute concentration in methane/air laminar premixed flat flame under different equivalence ratios at atmospheric pressure are investigated by using bi-directional laser-induced flu- orescence (LIF) detection scheme combined with the direct absorption spectroscopy. The effective peak absorption cross section and the average temperature at a height of 2 mm above the burner are obtained by exciting absorption on the Q1(8) rotational line in the A2∑+ (Dt = 0) ←- X2∏ (v = 0) at 309.240 nm. The measured values are 1.86×10-15 cm2 and 1719 K, respectively. Spatial filtering and frequency filtering methods of reducing noise are used to deal with the experi- mental data, and the smoothing effects are also compared using the two methods. The spatial distribution regularities of OH concentration are obtained with the equivalence ratios ranging from 0.8 to 1.3. The spatial resolution of the measured result is 84μm. Finally, a comparison is made between the experimental result of this paper and other relevant study results.展开更多
Bi-directional static loading test adopting load cells is widely used around the world at present, with increase in diameter and length of deep foundations. In this paper, a new simple conversion method to predict the...Bi-directional static loading test adopting load cells is widely used around the world at present, with increase in diameter and length of deep foundations. In this paper, a new simple conversion method to predict the equivalent pile head load-settlement curve considering elastic shortening of deep foundation was put forward according to the load transfer mechanism. The proposed conversion method was applied to root caisson foundation in a bridge and to large diameter pipe piles in a sea wind power plant. Some new load cells, test procedure, and construction technology were adopted based on the applications to different deep foundations, which could enlarge the application scopes of bi-directional loading test. A new type of bi-directional loading test for pipe pile was conducted, in which the load cell was installed and loaded after the pipe pile with special connector has been set up. Unlike the conventional bi-directional loading test, the load cell can be reused and shows an evident economic benefit.展开更多
基金financially supported by the State Key Laboratory of Structural Analysis,Optimization and CAE Software for Industrial Equipment,Dalian University of Technology(Grant No.GZ23112)the Shandong Provincial Natural Science Foundation,China(Grant No.ZR2021ME146).
文摘To predict the wave loads of a flexible trimaran in different wave fields,a one-way interaction numerical simulation method is proposed by integrating the fluid solver(Star-CCM+)and structural solver(Abaqus).Differing from the existing coupled CFD-FEA method for monohull ships in head waves,the presented method equates the mass and stiffness of the whole ship to the hull shell so that any transverse and longitudinal section stress of the hull in oblique waves can be obtained.Firstly,verification study and sensitivity analysis are carried out by comparing the trimaran motions using different mesh sizes and time step schemes.Discussion on the wave elevation of uni-and bi-directional waves is also carried out.Then a comprehensive analysis on the structural responses of the trimaran in different uni-directional regular wave and bi-directional cross sea conditions is carried out,respectively.Finally,the differences in structural response characteristics of trimaran in different wave fields are studied.The results show that the present method can reduce the computational burden of the two-way fluid-structure interaction simulations.
基金Project supported by the National Natural Science Foundation of China(Grant No.62061014)the Natural Science Foundation of Liaoning province of China(Grant No.2020-MS-274).
文摘Security during remote transmission has been an important concern for researchers in recent years.In this paper,a hierarchical encryption multi-image encryption scheme for people with different security levels is designed,and a multiimage encryption(MIE)algorithm with row and column confusion and closed-loop bi-directional diffusion is adopted in the paper.While ensuring secure communication of medical image information,people with different security levels have different levels of decryption keys,and differentiated visual effects can be obtained by using the strong sensitivity of chaotic keys.The highest security level can obtain decrypted images without watermarks,and at the same time,patient information and copyright attribution can be verified by obtaining watermark images.The experimental results show that the scheme is sufficiently secure as an MIE scheme with visualized differences and the encryption and decryption efficiency is significantly improved compared to other works.
基金supported by Yunnan Provincial Education Department Science Foundation of China under Grant construction of the seventh batch of key engineering research centers in colleges and universities(Grant Project:Yunnan College and University Edge Computing Network Engineering Research Center).
文摘Sentiment analysis,commonly called opinion mining or emotion artificial intelligence(AI),employs biometrics,computational linguistics,nat-ural language processing,and text analysis to systematically identify,extract,measure,and investigate affective states and subjective data.Sentiment analy-sis algorithms include emotion lexicon,traditional machine learning,and deep learning.In the text sentiment analysis algorithm based on a neural network,multi-layer Bi-directional long short-term memory(LSTM)is widely used,but the parameter amount of this model is too huge.Hence,this paper proposes a Bi-directional LSTM with a trapezoidal structure model.The design of the trapezoidal structure is derived from classic neural networks,such as LeNet-5 and AlexNet.These classic models have trapezoidal-like structures,and these structures have achieved success in the field of deep learning.There are two benefits to using the Bi-directional LSTM with a trapezoidal structure.One is that compared with the single-layer configuration,using the of the multi-layer structure can better extract the high-dimensional features of the text.Another is that using the trapezoidal structure can reduce the model’s parameters.This paper introduces the Bi-directional LSTM with a trapezoidal structure model in detail and uses Stanford sentiment treebank 2(STS-2)for experiments.It can be seen from the experimental results that the trapezoidal structure model and the normal structure model have similar performances.However,the trapezoidal structure model parameters are 35.75%less than the normal structure model.
基金funded by the National Natural Science Foundation of China(Grant No.51505096)the Natural Science Foundation of Heilongjiang Province(Grant No.LH2020E064).
文摘Natural frequency and dynamic stiffness under transient loading are two key performances for structural design related to automotive,aviation and construction industries.This article aims to tackle the multi-objective topological optimization problem considering dynamic stiffness and natural frequency using modified version of bi-directional evolutionary structural optimization(BESO).The conventional BESO is provided with constant evolutionary volume ratio(EVR),whereas low EVR greatly retards the optimization process and high EVR improperly removes the efficient elements.To address the issue,the modified BESO with variable EVR is introduced.To compromise the natural frequency and the dynamic stiffness,a weighting scheme of sensitivity numbers is employed to form the Pareto solution space.Several numerical examples demonstrate that the optimal solutions obtained from the modified BESO method have good agreement with those from the classic BESO method.Most importantly,the dynamic removal strategy with the variable EVR sharply springs up the optimization process.Therefore,it is concluded that the modified BESO method with variable EVR can solve structural design problems using multi-objective optimization.
基金Project supported by the National Natural Science Foundation of Sichuan Province of China(Nos. 2022NSFSC2003, 23NSFSC0849, and 2023NSFSC1300)。
文摘This study examines the wave propagation characteristics for a bi-directional functional grading of barium titanate(BaTiO_(3)) and cobalt ferrite(CoFe_(2)O_(4)) porous nanoshells,the porosity distribution of which is simulated by the honeycomb-shaped symmetrical and asymmetrical distribution functions.The nonlocal strain gradient theory(NSGT) and first-order shear deformation theory are used to determine the size effect and shear deformation,respectively.Nonlocal governing equations are derived for the nanoshells by Hamilton's principle.The resulting dimensionless differential equations are solved by means of an analytical solution of the combined exponential function after dimensionless treatment.Finally,extensive parametric surveys are conducted to investigate the influence of diverse parameters,such as dimensionless scale parameters,radiusto-thickness ratios,bi-directional functionally graded(FG) indices,porosity coefficients,and dimensionless electromagnetic potentials on the wave propagation characteristics.Based on the analysis results,the effect of the dimensionless scale parameters on the dispersion relationship is found to be related to the ratio of the scale parameters.The wave propagation characteristics of nanoshells in the presence of a magnetoelectric field depend on the bi-directional FG indices.
文摘Skin cancer diagnosis is difficult due to lesion presentation variability. Conventionalmethods struggle to manuallyextract features and capture lesions spatial and temporal variations. This study introduces a deep learning-basedConvolutional and Recurrent Neural Network (CNN-RNN) model with a ResNet-50 architecture which usedas the feature extractor to enhance skin cancer classification. Leveraging synergistic spatial feature extractionand temporal sequence learning, the model demonstrates robust performance on a dataset of 9000 skin lesionphotos from nine cancer types. Using pre-trained ResNet-50 for spatial data extraction and Long Short-TermMemory (LSTM) for temporal dependencies, the model achieves a high average recognition accuracy, surpassingprevious methods. The comprehensive evaluation, including accuracy, precision, recall, and F1-score, underscoresthe model’s competence in categorizing skin cancer types. This research contributes a sophisticated model andvaluable guidance for deep learning-based diagnostics, also this model excels in overcoming spatial and temporalcomplexities, offering a sophisticated solution for dermatological diagnostics research.
文摘Tunnel boring machines(TBMs)have been widely utilised in tunnel construction due to their high efficiency and reliability.Accurately predicting TBM performance can improve project time management,cost control,and risk management.This study aims to use deep learning to develop real-time models for predicting the penetration rate(PR).The models are built using data from the Changsha metro project,and their performances are evaluated using unseen data from the Zhengzhou Metro project.In one-step forecast,the predicted penetration rate follows the trend of the measured penetration rate in both training and testing.The autoregressive integrated moving average(ARIMA)model is compared with the recurrent neural network(RNN)model.The results show that univariate models,which only consider historical penetration rate itself,perform better than multivariate models that take into account multiple geological and operational parameters(GEO and OP).Next,an RNN variant combining time series of penetration rate with the last-step geological and operational parameters is developed,and it performs better than other models.A sensitivity analysis shows that the penetration rate is the most important parameter,while other parameters have a smaller impact on time series forecasting.It is also found that smoothed data are easier to predict with high accuracy.Nevertheless,over-simplified data can lose real characteristics in time series.In conclusion,the RNN variant can accurately predict the next-step penetration rate,and data smoothing is crucial in time series forecasting.This study provides practical guidance for TBM performance forecasting in practical engineering.
基金supported by the National Natural Science Foundation of China(61503407,61806219,61703426,61876189,61703412)the China Postdoctoral Science Foundation(2016 M602996)。
文摘The multi-agent system is the optimal solution to complex intelligent problems. In accordance with the game theory, the concept of loyalty is introduced to analyze the relationship between agents' individual income and global benefits and build the logical architecture of the multi-agent system. Besides, to verify the feasibility of the method, the cyclic neural network is optimized, the bi-directional coordination network is built as the training network for deep learning, and specific training scenes are simulated as the training background. After a certain number of training iterations, the model can learn simple strategies autonomously. Also,as the training time increases, the complexity of learning strategies rises gradually. Strategies such as obstacle avoidance, firepower distribution and collaborative cover are adopted to demonstrate the achievability of the model. The model is verified to be realizable by the examples of obstacle avoidance, fire distribution and cooperative cover. Under the same resource background, the model exhibits better convergence than other deep learning training networks, and it is not easy to fall into the local endless loop.Furthermore, the ability of the learning strategy is stronger than that of the training model based on rules, which is of great practical values.
基金financially supported by the National Key Research and Development Program of China(Grant No.2017YFC1404200)the Tianjin Key Program of Applied Foundation and Advanced-Tech Research,China(Grant No.18JCZDJC40200)+1 种基金the National High Technology Research and Development Program of China(863 Program,Grant No.2012AA051709)the National Natural Science Foundation of China(Grant No.51509183)
文摘The local scour around a new pile-group foundation of offshore wind turbine subjected to a bi-directional current was physically modeled with a bi-directional flow flume. In a series of experiments, the flow velocity and topography of the seabed were measured based on a system composed of plane positioning equipment and an ADV.Experimental results indicate that the development of the scour hole was fast at the beginning, but then the scour rate decreased until reaching equilibrium. Erosion would occur around each pile of the foundation. In most cases, the scour pits were connected in pairs and the outside widths of the scour holes were larger than the inner widths. The maximum scour depth occurred at the side pile of the foundation for each test. In addition, a preliminary investigation shows that the larger the flow velocity, the larger the scour hole dimensions but the shorter equilibrium time. The field maximum scour depth around the foundation was obtained based on the physical experiments with the geometric length scales of 1:27.0, 1:42.5 and 1:68.0, and it agrees with the scour depth estimated by the HEC-18 equation.
文摘The constitutive promoter of cauliflower mosaic virus 35S (CaMV 35S) is a polar unidirectional promoter and is widely used in plant genetic engineering. In the present study, the unidirectional CaMV 35S promoter has been modified to a bi-directional promoter by fusing its minimal promoter element to the 5' end of CaMV 35S promoter in the opposite orientation. To qualitatively and quantitatively estimate its bi-directional transcriptional function and activity, two visible reporter genes, gusA (13-glucuronidase, GUS) and gfp (green fluorescent protein, GFP), were fused to the two ends of the promoter in bi-orientations ending with NOS terminator sequences, respectively. Stable expression of gusA and gfp genes in transgenic tobacco (Nicotiana tabacum L.) was visulized by histochemically staining for GUS and fluorescence microscopic observation under UV for GFP in transgenic plants. The expression of two reporter genes showed that the constructed bi-directional promoter did have the bi-directional transcriptional function in both expected orientations. The quantitative estimation of GUS and GFP were determined on a HITACHI F1000 Fluorescence Spectrophotometer with various wavelengths of excitation and emission. The GUS activity varied from g to 250 pmol 4-MU/min/mg protein and the GFP content varied from 0.9 to 1.8 μg/ mg protein in various lines of transgenic tobacco plants. Higher GUS activity generally coupled with lower GFP content, and vice versa.
基金supported by the National Key Scientific Instrument and Equipment Development Projects of China(Grant No.2012YQ040164)the National Natural Science Foundation of China(Grant Nos.61275127 and 91441130)+1 种基金the China Postdoctoral Science Foundation(Grant No.2014M560262)the Postdoctoral Fellowship in Heilongjiang Province,China(Grant No.LBH-Z14074)
文摘The one-dimensional (1D) spatial distributions of OH absolute concentration in methane/air laminar premixed flat flame under different equivalence ratios at atmospheric pressure are investigated by using bi-directional laser-induced flu- orescence (LIF) detection scheme combined with the direct absorption spectroscopy. The effective peak absorption cross section and the average temperature at a height of 2 mm above the burner are obtained by exciting absorption on the Q1(8) rotational line in the A2∑+ (Dt = 0) ←- X2∏ (v = 0) at 309.240 nm. The measured values are 1.86×10-15 cm2 and 1719 K, respectively. Spatial filtering and frequency filtering methods of reducing noise are used to deal with the experi- mental data, and the smoothing effects are also compared using the two methods. The spatial distribution regularities of OH concentration are obtained with the equivalence ratios ranging from 0.8 to 1.3. The spatial resolution of the measured result is 84μm. Finally, a comparison is made between the experimental result of this paper and other relevant study results.
基金Supported by the National Natural Science Foundation of China (50908048)the Priority Academic Program Development (PAPD) Project of JiangsuHigher Education Institutions
文摘Bi-directional static loading test adopting load cells is widely used around the world at present, with increase in diameter and length of deep foundations. In this paper, a new simple conversion method to predict the equivalent pile head load-settlement curve considering elastic shortening of deep foundation was put forward according to the load transfer mechanism. The proposed conversion method was applied to root caisson foundation in a bridge and to large diameter pipe piles in a sea wind power plant. Some new load cells, test procedure, and construction technology were adopted based on the applications to different deep foundations, which could enlarge the application scopes of bi-directional loading test. A new type of bi-directional loading test for pipe pile was conducted, in which the load cell was installed and loaded after the pipe pile with special connector has been set up. Unlike the conventional bi-directional loading test, the load cell can be reused and shows an evident economic benefit.