This paper presents the results of an ongoing investigation into the fluctuations of pressure signals due to solids-gas flows for dense-phase pneumatic conveying of fine powders. Pressure signals were obtained from pr...This paper presents the results of an ongoing investigation into the fluctuations of pressure signals due to solids-gas flows for dense-phase pneumatic conveying of fine powders. Pressure signals were obtained from pressure transducers installed along different locations of a pipeline for the fluidized dense-phase pneumatic conveying of fly ash （median particle diameter 30μm; particle density 2300 kg/m^3; loose- poured bulk density 700 kg/m^3） and white powder （median particle diameter 55 p.m; particle density 1600 kg/m^3 ; loose-poured bulk density 620 kg/m^3） from dilute to fluidized dense-phase. Standard deviation and Shannon entropy were employed to investigate the pressure signal fluctuations. It was found that there is an increase in the values of Shannon entropy and standard deviation for both of the prod- ucts along the flow direction through the straight pipe sections. However, both the Shannon entropy and standard deviation values tend to decrease after the flow through bend（s）, This result could be attributed to the deceleration of particles while flowing through the bends, resulting in dampened particle fluctua- tion and turbulence. Lower values of Shannon entropy in the early parts of the pipeline could be due to the non-suspension nature of flow （dense-phase）, i.e., there is a higher probability that the particles are concentrated toward the bottom of pipe, compared with dilute-phase or suspension flow （high velocity）, where the particles could be expected to be distributed homogenously throughout the pipe bore （as the flow is in suspension）. Changes in straight-pipe pneumatic conveying characteristics along the flow direction also indicate a change in the flow regime along the flow.展开更多
In order to minimize uncertainty of the inversed parameters to the largest extent by making full use of the limited information in remote sensing data, it is necessary to understand what the information flow in quanti...In order to minimize uncertainty of the inversed parameters to the largest extent by making full use of the limited information in remote sensing data, it is necessary to understand what the information flow in quantitative remote sensing model inversion is, thus control the information flow. Aiming at this, the paper takes the linear kernel-driven model inversion as an example. At first, the information flow in different inversion methods is calculated and analyzed, then the effect of information flow controlled by multi-stage inversion strategy is studied, finally, an information matrix based on USM is defined to control information flow in inversion. It shows that using Shannon entropy decrease of the inversed parameters can express information flow more properly. Changing the weight of a priori knowledge in inversion or fixing parameters and partitioning datasets in multi-stage inversion strategy can control information flow. In regularization inversion of remote sensing, information matrix based on USM may be a better tool for quantitatively controlling information flow.展开更多
Based on a group of axioms, a measure of information discrepancyamong multiple information sources has been introduced in and it possesses some peculiar properties compared with other measures of information discrepa...Based on a group of axioms, a measure of information discrepancyamong multiple information sources has been introduced in and it possesses some peculiar properties compared with other measures of information discrepancy, so it can be used in some areas, where the traditional measures are not valid or not efficient, for example, in the study of DNA sequence comparison, prediction of protein structure class, evidence analysis, questionnaire analysis, and so on. In this paper, using the optimization techniques, we prove that it is a distance function and show that it is also an approximation of χ2 function. These two properties will stimulate further applications of the measure to information processing and system analysis.展开更多
Map is one of the communication means created by human being.Cartographers have been making efforts on the comparison of maps to natural languages so as to establish a"cartographic language"or"map langu...Map is one of the communication means created by human being.Cartographers have been making efforts on the comparison of maps to natural languages so as to establish a"cartographic language"or"map language".One of such efforts is to adopt the Shannon’s Information Theory originated in digital communication into cartography so as to establish an entropy-based cartographic communication theory.However,success has been very limited although research work had started as early as the mid-1960 s.It is then found that the bottleneck problem was the lack of appropriate measures for the spatial(configurational)information of(graphic and image)maps,as the classic Shannon entropy is only capable of characterizing statistical information but fails to capture the configurational information of(graphic and image)maps.Fortunately,after over 40-year development,some bottleneck problems have been solved.More precisely,generalized Shannon entropies for metric and thematic information of(graphic)maps have been developed and the first feasible solution for computing the Boltzmann entropy of image maps has been invented,which is capable of measuring the spatial information of not only numerical images but also categorical maps.With such progress,it is now feasible to build the"Information Theory of Cartography".In this paper,a framework for such a theory is proposed and some key issues are identified.For these issues,some have already been tackled while others still need efforts.As a result,a research agenda is set for future action.After all these issues are tackled,the theory will become matured so as to become a theoretic basis of cartography.It is expected that the Information Theory of Cartography will play an increasingly important role in the discipline of cartography because more and more researchers have advocated that information is more fundamental than matter and energy.展开更多
Microbial functional diversity and enzymatic activities are critical to maintaining material circulation during litter decomposition in forests.Thinning,an important and widely used silvicultural treatment,changes the...Microbial functional diversity and enzymatic activities are critical to maintaining material circulation during litter decomposition in forests.Thinning,an important and widely used silvicultural treatment,changes the microclimate and promotes forest renewal.However,how thinning affects microbial functional diversity and enzymatic activities during litter decomposition remains poorly understood.We conducted thinning treatments in a Chinese fir plantation in a subtropical region of China with four levels of tree stem removal（0,30,50,and 70%）,each with three replicates,and the effects of thinning on microbial functional diversity and enzymatic activities were studied 7 years after treatment by collecting litter samples four times over a 1-year period.Microbial functional diversity and enzymatic activities were analyzed using Biolog Ecoplates（Biolog Inc.,Hayward,CA,USA）based on the utilization of 31 carbon substrates.Total microbial abundance during litter decomposition was lower after the thinning treatments than without thinning.Microbial functional diversity did not differ significantly during litter decomposition,but the types of microbial carbon-source utilization did differ significantly with the thinning treatments.Microbial cellulase and invertase activities during litter decomposition were significantly higher under the thinning treatments due to changes in the litter carbon concentration and the ratios of carbon and lignin to nitrogen.The present study demonstrated the important influence of thinning on microbial activities during litter decomposition.Moderate-intensity thinning may maximize vegetation diversity and,in turn,increase the available substrate sources for microbial organisms in litter and promote nutrient cycling in forest ecosystems.展开更多
Piezoelectric sensor array-based spatial filter technology is a new promising method presented in research area of structural health monitoring （SHM） in the recent years. To apply this method to composite structures...Piezoelectric sensor array-based spatial filter technology is a new promising method presented in research area of structural health monitoring （SHM） in the recent years. To apply this method to composite structures and give the actual position of damage, this paper proposes a spatial filter-based damage imaging method improved by complex Shannon wavelet transform. The basic principle of spatial filter is analyzed first. Then, this paper proposes a method of using complex Shannon wavelet transform to construct analytic signals of time domain signals of PZT sensors array. The analytic signals are synthesized depending on the principle of the spatial filter to give a damage imaging in the form of angle-time. A method of converting the damage imaging to the form of angle-distance is discussed. Finally, an aircraft composite oil tank is adopted to validate the damage imaging method. The validating results show that this method can recognize angle and distance of damage successfully.展开更多
In digital signal processing (DSP), Nyquistrate sampling completely describes a signal by exploiting its bandlimitedness. Compressed Sensing (CS), also known as compressive sampling, is a DSP technique efficiently acq...In digital signal processing (DSP), Nyquistrate sampling completely describes a signal by exploiting its bandlimitedness. Compressed Sensing (CS), also known as compressive sampling, is a DSP technique efficiently acquiring and reconstructing a signal completely from reduced number of measurements, by exploiting its compressibility. The measurements are not point samples but more general linear functions of the signal. CS can capture and represent sparse signals at a rate significantly lower than ordinarily used in the Shannon’s sampling theorem. It is interesting to notice that most signals in reality are sparse;especially when they are represented in some domain (such as the wavelet domain) where many coefficients are close to or equal to zero. A signal is called K-sparse, if it can be exactly represented by a basis, , and a set of coefficients , where only K coefficients are nonzero. A signal is called approximately K-sparse, if it can be represented up to a certain accuracy using K non-zero coefficients. As an example, a K-sparse signal is the class of signals that are the sum of K sinusoids chosen from the N harmonics of the observed time interval. Taking the DFT of any such signal would render only K non-zero values . An example of approximately sparse signals is when the coefficients , sorted by magnitude, decrease following a power law. In this case the sparse approximation constructed by choosing the K largest coefficients is guaranteed to have an approximation error that decreases with the same power law as the coefficients. The main limitation of CS-based systems is that they are employing iterative algorithms to recover the signal. The sealgorithms are slow and the hardware solution has become crucial for higher performance and speed. This technique enables fewer data samples than traditionally required when capturing a signal with relatively high bandwidth, but a low information rate. As a main feature of CS, efficient algorithms such as -minimization can be used for recovery. This paper gives a su展开更多
When multiphysics coupling calculations contain time-dependent Monte Carlo particle transport simulations, these simulations often account for the largest part of the calculation time, which is insufferable in certain...When multiphysics coupling calculations contain time-dependent Monte Carlo particle transport simulations, these simulations often account for the largest part of the calculation time, which is insufferable in certain important cases. This study proposes an adaptive strategy for automatically adjusting the sample size to fulfil more reasonable simulations. This is realized based on an extension of the Shannon entropy concept and is essentially different from the popular methods in timeindependent Monte Carlo particle transport simulations, such as controlling the sample size according to the relative error of a target tally or by experience. The results of the two models show that this strategy can yield almost similar results while significantly reducing the calculation time. Considering the efficiency, the sample size should not be increased blindly if the efficiency cannot be enhanced further. The strategy proposed herein satisfies this requirement.展开更多
The concept of pedodiversity and its measurement methodology proposed and developed by Ibá?ez research term is introduced. An attempt to apply pedodiversity to analyze spatial soil variation and distribution patt...The concept of pedodiversity and its measurement methodology proposed and developed by Ibá?ez research term is introduced. An attempt to apply pedodiversity to analyze spatial soil variation and distribution patterns on the global scale is briefly demonstrated. Furthermore, constructive comments and criticisms on pedodiversity and its measurement from the noted pedologists and ecologists are outlined. Finally, potential applications of pedodiversity in soil science and other relevant disciplines are discussed.展开更多
Habitat quality is an important indicator for evaluating the quality of ecosystem.The Qinghai Province section of the Yellow River Basin plays an important role in the ecological protection of the upper reaches of the...Habitat quality is an important indicator for evaluating the quality of ecosystem.The Qinghai Province section of the Yellow River Basin plays an important role in the ecological protection of the upper reaches of the Yellow River Basin.To comprehensively analysis the alterations of habitat quality in the Qinghai Province section of the Yellow River Basin,this study utilized the Integrated Valuation of Ecosystem Services and Tradeoffs(InVEST)model to calculate the habitat quality index and analyze the spatio-temporal variation characteristics of habitat quality in the study area from 2000 to 2022,and calculated seven landscape pattern indices(number of patches,patch density,largest patch index(LPI),landscape shape index(LSI),contagion index(CONTAG),Shannon diversity index,and Shannon evenness index)to research the variation of landscape pattern in the study area.The results showed that the number of patches,patch density,LPI,LSI,Shannon diversity index,and Shannon evenness index increased from 2000 to 2022,while the CONTAG decreased,indicating that the landscape pattern in the Qinghai Province section of the Yellow River Basin changed in the direction of distribution fragmentation,shape complexity,and heterogeneity.The average value of the habitat quality index in the Qinghai Province section of the Yellow River Basin from 2000 to 2022 was 0.90.Based on the value of habitat quality index,we divided the level of habitat quality into five categories:lower(0.00-0.20),low(0.20-0.40),moderate(0.40-0.60),high(0.60-0.80),and higher(0.80-1.00).Most areas were at the higher habitat quality level.The lower habitat quality patches were mainly distributed in Longyang Gorge and Yellow River-Huangshui River Valley.From 2000 to 2022,the habitat quality in most areas was stable;the increase areas were mainly distributed in Guinan County,while the decrease areas were mainly distributed in Xining City,Maqen County,Xinghai County,Qumarleb County,and Darlag County.To show the extent of habitat quality variation,we calculated Sen ind展开更多
The analysis of microstates in EEG signals is a crucial technique for understanding the spatiotemporal dynamics of brain electrical activity.Traditional methods such as Atomic Agglomerative Hierarchical Clustering(AAH...The analysis of microstates in EEG signals is a crucial technique for understanding the spatiotemporal dynamics of brain electrical activity.Traditional methods such as Atomic Agglomerative Hierarchical Clustering(AAHC),K-means clustering,Principal Component Analysis(PCA),and Independent Component Analysis(ICA)are limited by a fixed number of microstate maps and insufficient capability in cross-task feature extraction.Tackling these limitations,this study introduces a Global Map Dissimilarity(GMD)-driven density canopy K-means clustering algorithm.This innovative approach autonomously determines the optimal number of EEG microstate topographies and employs Gaussian kernel density estimation alongside the GMD index for dynamic modeling of EEG data.Utilizing this advanced algorithm,the study analyzes the Motor Imagery(MI)dataset from the GigaScience database,GigaDB.The findings reveal six distinct microstates during actual right-hand movement and five microstates across other task conditions,with microstate C showing superior performance in all task states.During imagined movement,microstate A was significantly enhanced.Comparison with existing algorithms indicates a significant improvement in clustering performance by the refined method,with an average Calinski-Harabasz Index(CHI)of 35517.29 and a Davis-Bouldin Index(DBI)average of 2.57.Furthermore,an information-theoretical analysis of the microstate sequences suggests that imagined movement exhibits higher complexity and disorder than actual movement.By utilizing the extracted microstate sequence parameters as features,the improved algorithm achieved a classification accuracy of 98.41%in EEG signal categorization for motor imagery.A performance of 78.183%accuracy was achieved in a four-class motor imagery task on the BCI-IV-2a dataset.These results demonstrate the potential of the advanced algorithm in microstate analysis,offering a more effective tool for a deeper understanding of the spatiotemporal features of EEG signals.展开更多
The purpose of this paper is to assess the operational efficiency of a public bus transportation via a case study from a company in a large city of China by using data envelopment analysis(DEA)model and Shannon’s ent...The purpose of this paper is to assess the operational efficiency of a public bus transportation via a case study from a company in a large city of China by using data envelopment analysis(DEA)model and Shannon’s entropy.This company operates 37 main routes on the backbone roads.Thus,it plays a significant role in public transportation in the city.According to bus industry norms,an efficiency evaluation index system is constructed from the perspective of both company operations and passenger demands.For passenger satisfaction,passenger waiting time and passenger-crowding degree are considered,and they are undesirable indicators.To describe such indicators,a superefficient DEA model is constructed.With this model,by using actual data,efficiency is evaluated for each bus route.Results show that the DEA model with Shannon’s entropy being combined achieves more reasonable results.Also,sensitivity analysis is presented.Therefore,the results are meaningful for the company to improve its operations and management.展开更多
The behavior of the Kozachenko–Leonenko estimates for the(differential) Shannon entropy is studied when the number of i.i.d. vector-valued observations tends to infinity. The asymptotic unbiasedness and L^2-consisten...The behavior of the Kozachenko–Leonenko estimates for the(differential) Shannon entropy is studied when the number of i.i.d. vector-valued observations tends to infinity. The asymptotic unbiasedness and L^2-consistency of the estimates are established. The conditions employed involve the analogues of the Hardy–Littlewood maximal function. It is shown that the results are valid in particular for the entropy estimation of any nondegenerate Gaussian vector.展开更多
Mushrooms have a remarkable scientific value due to their nutritional, medicinal properties and industrial applications in enzyme production, so that effort in the maintenance of native wild mushroom varieties is incr...Mushrooms have a remarkable scientific value due to their nutritional, medicinal properties and industrial applications in enzyme production, so that effort in the maintenance of native wild mushroom varieties is increasing. The present study focuses on the use of Random Amplified Polymorphic DNA (RAPD) markers for biodiversity measure of wild mushroom species of the Northwest mountainous region of Greece. Data mining of similarity matrices from RAPD analysis was used to extract measurable entropy parameters for mushroom biodiversity monitoring based on Shannon’s information entropy. Shannon information index provides an easy assessment of the entropy of the genetic information of the germplasm per mushroom species while the total equitability index (E<sub>H</sub>) = 0.871 offers an overall estimation of the genetic variation evenness of all species in the population of the studied mushrooms. Application of RAPDs with parallel entropy analysis is an easily applicable and low-cost valuable technology in environmental monitoring, using genetic information of wild mushroom species as an indicator that can lead to future actions in biodiversity maintenance and germplasm protection. The provided methodology can serve as a pilot procedure enriched with other environmental factors to monitor and protect wild mushroom communities native to the Greek countryside or in any part of the world and provide comparable results about biodiversity from different regions using common entropy indices.展开更多
Two typical provincial capitals （Nanjing and Zhengzhou） and two counties （Rugao and Yuanyang） in east （Jiangsu Province） and central （Henan Province） China were chosen respectively as the developed and less de...Two typical provincial capitals （Nanjing and Zhengzhou） and two counties （Rugao and Yuanyang） in east （Jiangsu Province） and central （Henan Province） China were chosen respectively as the developed and less developed comparative cases for pedodiversity and land use diversity correlative analysis by borrowing the recently better developed pedodiversity methodology. Land use classification was worked out using remote sensing images in three different periods （1986-1988, 2000-2001 and 2004-2006） for these studied case areas before the calculation of the constituent diversity index and spatial distribution diversity index modified after Shannon entropy in 2 kmx2 km grid scale of the soil and land use pattern were conducted and then a connection index was proposed to evaluate the relationship between soil and land use diversity. Results show that during the years from 1986 to 2006, the composition and spatial distribution of regional land use pattern had changed greatly. The agricultural land area of all the studied case areas decreased obviously in which Nanjing has the highest decrement of 895.98 km2 mainly into urban use while the other land use type area changes show the same trend. The connection index of four typical soil family types and typical urban land use types, i.e., urban construction land, transportation land and industrial and mining area all increased in this period. In the studied case areas, there is the highest soil constituent diversity in Zhengzhou at 0.779 while the simplest soil constituent diversity in Rugao at 0.582. Meanwhile we have higher land use diversity in the more urbanized Jiangsu Province than Henan Province, Nanjing is ranking the first that has been getting higher and higher in the three periods at 0.366 in 1986-1988, 0.483 in 2000-2001 and 0.545 in 2004-2006. Finally, the connection index figures to evaluate the relationship between soil and land use diversity of the studied areas were compared to show the similar phenomenon that this figure grows fastest in N展开更多
In recent years we extended Shannon static statistical information theory to dynamic processes and established a Shannon dynamic statistical information theory, whose core is the evolution law of dynamic entropy and d...In recent years we extended Shannon static statistical information theory to dynamic processes and established a Shannon dynamic statistical information theory, whose core is the evolution law of dynamic entropy and dynamic information. We also proposed a corresponding Boltzmman dynamic statistical information theory. Based on the fact that the state variable evolution equation of respective dynamic systems, i.e. Fok- ker-Planck equation and Liouville diffusion equation can be regarded as their information symbol evolution equation, we derived the nonlinear evolution equations of Shannon dy- namic entropy density and dynamic information density and the nonlinear evolution equa- tions of Boltzmann dynamic entropy density and dynamic information density, that de- scribe respectively the evolution law of dynamic entropy and dynamic information. The evolution equations of these two kinds of dynamic entropies and dynamic informations show in unison that the time rate of change of dynamic entropy densities is caused by their drift, diffusion and production in state variable space inside the systems and coordinate space in the transmission processes; and that the time rate of change of dynamic infor- mation densities originates from their drift, diffusion and dissipation in state variable space inside the systems and coordinate space in the transmission processes. Entropy and in- formation have been combined with the state and its law of motion of the systems. Fur- thermore we presented the formulas of two kinds of entropy production rates and infor- mation dissipation rates, the expressions of two kinds of drift information flows and diffu- sion information flows. We proved that two kinds of information dissipation rates (or the decrease rates of the total information) were equal to their corresponding entropy produc- tion rates (or the increase rates of the total entropy) in the same dynamic system. We obtained the formulas of two kinds of dynamic mutual informations and dynamic channel capacities reflecting the dynam展开更多
文摘This paper presents the results of an ongoing investigation into the fluctuations of pressure signals due to solids-gas flows for dense-phase pneumatic conveying of fine powders. Pressure signals were obtained from pressure transducers installed along different locations of a pipeline for the fluidized dense-phase pneumatic conveying of fly ash （median particle diameter 30μm; particle density 2300 kg/m^3; loose- poured bulk density 700 kg/m^3） and white powder （median particle diameter 55 p.m; particle density 1600 kg/m^3 ; loose-poured bulk density 620 kg/m^3） from dilute to fluidized dense-phase. Standard deviation and Shannon entropy were employed to investigate the pressure signal fluctuations. It was found that there is an increase in the values of Shannon entropy and standard deviation for both of the prod- ucts along the flow direction through the straight pipe sections. However, both the Shannon entropy and standard deviation values tend to decrease after the flow through bend（s）, This result could be attributed to the deceleration of particles while flowing through the bends, resulting in dampened particle fluctua- tion and turbulence. Lower values of Shannon entropy in the early parts of the pipeline could be due to the non-suspension nature of flow （dense-phase）, i.e., there is a higher probability that the particles are concentrated toward the bottom of pipe, compared with dilute-phase or suspension flow （high velocity）, where the particles could be expected to be distributed homogenously throughout the pipe bore （as the flow is in suspension）. Changes in straight-pipe pneumatic conveying characteristics along the flow direction also indicate a change in the flow regime along the flow.
基金This work was supported by the Special Funds for the Major State Basic Research Project(Grant No.G2000077903)the National Natural Science Foundation of China(Grant No.40171068).
文摘In order to minimize uncertainty of the inversed parameters to the largest extent by making full use of the limited information in remote sensing data, it is necessary to understand what the information flow in quantitative remote sensing model inversion is, thus control the information flow. Aiming at this, the paper takes the linear kernel-driven model inversion as an example. At first, the information flow in different inversion methods is calculated and analyzed, then the effect of information flow controlled by multi-stage inversion strategy is studied, finally, an information matrix based on USM is defined to control information flow in inversion. It shows that using Shannon entropy decrease of the inversed parameters can express information flow more properly. Changing the weight of a priori knowledge in inversion or fixing parameters and partitioning datasets in multi-stage inversion strategy can control information flow. In regularization inversion of remote sensing, information matrix based on USM may be a better tool for quantitatively controlling information flow.
基金Thiswork issupported by National Natural Science Foundation of China(90 10 30 33,39830 0 70 ) andNKBRSF (G19980 30 60 )
文摘Based on a group of axioms, a measure of information discrepancyamong multiple information sources has been introduced in and it possesses some peculiar properties compared with other measures of information discrepancy, so it can be used in some areas, where the traditional measures are not valid or not efficient, for example, in the study of DNA sequence comparison, prediction of protein structure class, evidence analysis, questionnaire analysis, and so on. In this paper, using the optimization techniques, we prove that it is a distance function and show that it is also an approximation of χ2 function. These two properties will stimulate further applications of the measure to information processing and system analysis.
基金National Natural Science Foundation of China(Nos.41930104,41971330)Hong Kong Research Grants Council General Research Fund(No.152219/18E)。
文摘Map is one of the communication means created by human being.Cartographers have been making efforts on the comparison of maps to natural languages so as to establish a"cartographic language"or"map language".One of such efforts is to adopt the Shannon’s Information Theory originated in digital communication into cartography so as to establish an entropy-based cartographic communication theory.However,success has been very limited although research work had started as early as the mid-1960 s.It is then found that the bottleneck problem was the lack of appropriate measures for the spatial(configurational)information of(graphic and image)maps,as the classic Shannon entropy is only capable of characterizing statistical information but fails to capture the configurational information of(graphic and image)maps.Fortunately,after over 40-year development,some bottleneck problems have been solved.More precisely,generalized Shannon entropies for metric and thematic information of(graphic)maps have been developed and the first feasible solution for computing the Boltzmann entropy of image maps has been invented,which is capable of measuring the spatial information of not only numerical images but also categorical maps.With such progress,it is now feasible to build the"Information Theory of Cartography".In this paper,a framework for such a theory is proposed and some key issues are identified.For these issues,some have already been tackled while others still need efforts.As a result,a research agenda is set for future action.After all these issues are tackled,the theory will become matured so as to become a theoretic basis of cartography.It is expected that the Information Theory of Cartography will play an increasingly important role in the discipline of cartography because more and more researchers have advocated that information is more fundamental than matter and energy.
基金financed by a project funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD)the Research Innovation Program for College Graduates of Jiangsu Province,China(KYLX16_0832)
文摘Microbial functional diversity and enzymatic activities are critical to maintaining material circulation during litter decomposition in forests.Thinning,an important and widely used silvicultural treatment,changes the microclimate and promotes forest renewal.However,how thinning affects microbial functional diversity and enzymatic activities during litter decomposition remains poorly understood.We conducted thinning treatments in a Chinese fir plantation in a subtropical region of China with four levels of tree stem removal（0,30,50,and 70%）,each with three replicates,and the effects of thinning on microbial functional diversity and enzymatic activities were studied 7 years after treatment by collecting litter samples four times over a 1-year period.Microbial functional diversity and enzymatic activities were analyzed using Biolog Ecoplates（Biolog Inc.,Hayward,CA,USA）based on the utilization of 31 carbon substrates.Total microbial abundance during litter decomposition was lower after the thinning treatments than without thinning.Microbial functional diversity did not differ significantly during litter decomposition,but the types of microbial carbon-source utilization did differ significantly with the thinning treatments.Microbial cellulase and invertase activities during litter decomposition were significantly higher under the thinning treatments due to changes in the litter carbon concentration and the ratios of carbon and lignin to nitrogen.The present study demonstrated the important influence of thinning on microbial activities during litter decomposition.Moderate-intensity thinning may maximize vegetation diversity and,in turn,increase the available substrate sources for microbial organisms in litter and promote nutrient cycling in forest ecosystems.
基金National Natural Science Foundation of China (50830201,10872217)Aeronautical Science Foundation of China (20090952015)+1 种基金Specialized Research Fund for the Doctoral Program of Higher Education(20103218110005)National Science Foundation of the General Program of Jiangsu Higher Education Institutions (09KJD520005)
文摘Piezoelectric sensor array-based spatial filter technology is a new promising method presented in research area of structural health monitoring （SHM） in the recent years. To apply this method to composite structures and give the actual position of damage, this paper proposes a spatial filter-based damage imaging method improved by complex Shannon wavelet transform. The basic principle of spatial filter is analyzed first. Then, this paper proposes a method of using complex Shannon wavelet transform to construct analytic signals of time domain signals of PZT sensors array. The analytic signals are synthesized depending on the principle of the spatial filter to give a damage imaging in the form of angle-time. A method of converting the damage imaging to the form of angle-distance is discussed. Finally, an aircraft composite oil tank is adopted to validate the damage imaging method. The validating results show that this method can recognize angle and distance of damage successfully.
文摘In digital signal processing (DSP), Nyquistrate sampling completely describes a signal by exploiting its bandlimitedness. Compressed Sensing (CS), also known as compressive sampling, is a DSP technique efficiently acquiring and reconstructing a signal completely from reduced number of measurements, by exploiting its compressibility. The measurements are not point samples but more general linear functions of the signal. CS can capture and represent sparse signals at a rate significantly lower than ordinarily used in the Shannon’s sampling theorem. It is interesting to notice that most signals in reality are sparse;especially when they are represented in some domain (such as the wavelet domain) where many coefficients are close to or equal to zero. A signal is called K-sparse, if it can be exactly represented by a basis, , and a set of coefficients , where only K coefficients are nonzero. A signal is called approximately K-sparse, if it can be represented up to a certain accuracy using K non-zero coefficients. As an example, a K-sparse signal is the class of signals that are the sum of K sinusoids chosen from the N harmonics of the observed time interval. Taking the DFT of any such signal would render only K non-zero values . An example of approximately sparse signals is when the coefficients , sorted by magnitude, decrease following a power law. In this case the sparse approximation constructed by choosing the K largest coefficients is guaranteed to have an approximation error that decreases with the same power law as the coefficients. The main limitation of CS-based systems is that they are employing iterative algorithms to recover the signal. The sealgorithms are slow and the hardware solution has become crucial for higher performance and speed. This technique enables fewer data samples than traditionally required when capturing a signal with relatively high bandwidth, but a low information rate. As a main feature of CS, efficient algorithms such as -minimization can be used for recovery. This paper gives a su
基金supported by the CAEP Found (No.CX20200028)Youth Program of National Natural Science Foundation of China (No.11705011).
文摘When multiphysics coupling calculations contain time-dependent Monte Carlo particle transport simulations, these simulations often account for the largest part of the calculation time, which is insufferable in certain important cases. This study proposes an adaptive strategy for automatically adjusting the sample size to fulfil more reasonable simulations. This is realized based on an extension of the Shannon entropy concept and is essentially different from the popular methods in timeindependent Monte Carlo particle transport simulations, such as controlling the sample size according to the relative error of a target tally or by experience. The results of the two models show that this strategy can yield almost similar results while significantly reducing the calculation time. Considering the efficiency, the sample size should not be increased blindly if the efficiency cannot be enhanced further. The strategy proposed herein satisfies this requirement.
文摘The concept of pedodiversity and its measurement methodology proposed and developed by Ibá?ez research term is introduced. An attempt to apply pedodiversity to analyze spatial soil variation and distribution patterns on the global scale is briefly demonstrated. Furthermore, constructive comments and criticisms on pedodiversity and its measurement from the noted pedologists and ecologists are outlined. Finally, potential applications of pedodiversity in soil science and other relevant disciplines are discussed.
基金supported by the Demonstration Project of Integrated Ecological Rehabilitation Technology for Key Soil and Water Erosion Areas in the Yellow River Valley(2021-SF-134).
文摘Habitat quality is an important indicator for evaluating the quality of ecosystem.The Qinghai Province section of the Yellow River Basin plays an important role in the ecological protection of the upper reaches of the Yellow River Basin.To comprehensively analysis the alterations of habitat quality in the Qinghai Province section of the Yellow River Basin,this study utilized the Integrated Valuation of Ecosystem Services and Tradeoffs(InVEST)model to calculate the habitat quality index and analyze the spatio-temporal variation characteristics of habitat quality in the study area from 2000 to 2022,and calculated seven landscape pattern indices(number of patches,patch density,largest patch index(LPI),landscape shape index(LSI),contagion index(CONTAG),Shannon diversity index,and Shannon evenness index)to research the variation of landscape pattern in the study area.The results showed that the number of patches,patch density,LPI,LSI,Shannon diversity index,and Shannon evenness index increased from 2000 to 2022,while the CONTAG decreased,indicating that the landscape pattern in the Qinghai Province section of the Yellow River Basin changed in the direction of distribution fragmentation,shape complexity,and heterogeneity.The average value of the habitat quality index in the Qinghai Province section of the Yellow River Basin from 2000 to 2022 was 0.90.Based on the value of habitat quality index,we divided the level of habitat quality into five categories:lower(0.00-0.20),low(0.20-0.40),moderate(0.40-0.60),high(0.60-0.80),and higher(0.80-1.00).Most areas were at the higher habitat quality level.The lower habitat quality patches were mainly distributed in Longyang Gorge and Yellow River-Huangshui River Valley.From 2000 to 2022,the habitat quality in most areas was stable;the increase areas were mainly distributed in Guinan County,while the decrease areas were mainly distributed in Xining City,Maqen County,Xinghai County,Qumarleb County,and Darlag County.To show the extent of habitat quality variation,we calculated Sen ind
基金funded by National Nature Science Foundation of China,Yunnan Funda-Mental Research Projects,Special Project of Guangdong Province in Key Fields of Ordinary Colleges and Universities and Chaozhou Science and Technology Plan Project of Funder Grant Numbers 82060329,202201AT070108,2023ZDZX2038 and 202201GY01.
文摘The analysis of microstates in EEG signals is a crucial technique for understanding the spatiotemporal dynamics of brain electrical activity.Traditional methods such as Atomic Agglomerative Hierarchical Clustering(AAHC),K-means clustering,Principal Component Analysis(PCA),and Independent Component Analysis(ICA)are limited by a fixed number of microstate maps and insufficient capability in cross-task feature extraction.Tackling these limitations,this study introduces a Global Map Dissimilarity(GMD)-driven density canopy K-means clustering algorithm.This innovative approach autonomously determines the optimal number of EEG microstate topographies and employs Gaussian kernel density estimation alongside the GMD index for dynamic modeling of EEG data.Utilizing this advanced algorithm,the study analyzes the Motor Imagery(MI)dataset from the GigaScience database,GigaDB.The findings reveal six distinct microstates during actual right-hand movement and five microstates across other task conditions,with microstate C showing superior performance in all task states.During imagined movement,microstate A was significantly enhanced.Comparison with existing algorithms indicates a significant improvement in clustering performance by the refined method,with an average Calinski-Harabasz Index(CHI)of 35517.29 and a Davis-Bouldin Index(DBI)average of 2.57.Furthermore,an information-theoretical analysis of the microstate sequences suggests that imagined movement exhibits higher complexity and disorder than actual movement.By utilizing the extracted microstate sequence parameters as features,the improved algorithm achieved a classification accuracy of 98.41%in EEG signal categorization for motor imagery.A performance of 78.183%accuracy was achieved in a four-class motor imagery task on the BCI-IV-2a dataset.These results demonstrate the potential of the advanced algorithm in microstate analysis,offering a more effective tool for a deeper understanding of the spatiotemporal features of EEG signals.
基金supported in part by the Science and Technology Development Fund(FDCT),Macao SAR(0017/2019/A1,0002/2020/AKP)in part by the National Natural Science Foundation of China(61803397)。
文摘The purpose of this paper is to assess the operational efficiency of a public bus transportation via a case study from a company in a large city of China by using data envelopment analysis(DEA)model and Shannon’s entropy.This company operates 37 main routes on the backbone roads.Thus,it plays a significant role in public transportation in the city.According to bus industry norms,an efficiency evaluation index system is constructed from the perspective of both company operations and passenger demands.For passenger satisfaction,passenger waiting time and passenger-crowding degree are considered,and they are undesirable indicators.To describe such indicators,a superefficient DEA model is constructed.With this model,by using actual data,efficiency is evaluated for each bus route.Results show that the DEA model with Shannon’s entropy being combined achieves more reasonable results.Also,sensitivity analysis is presented.Therefore,the results are meaningful for the company to improve its operations and management.
基金Supported by the Russian Science Foundation(Grant No.14-21-00162)
文摘The behavior of the Kozachenko–Leonenko estimates for the(differential) Shannon entropy is studied when the number of i.i.d. vector-valued observations tends to infinity. The asymptotic unbiasedness and L^2-consistency of the estimates are established. The conditions employed involve the analogues of the Hardy–Littlewood maximal function. It is shown that the results are valid in particular for the entropy estimation of any nondegenerate Gaussian vector.
文摘Mushrooms have a remarkable scientific value due to their nutritional, medicinal properties and industrial applications in enzyme production, so that effort in the maintenance of native wild mushroom varieties is increasing. The present study focuses on the use of Random Amplified Polymorphic DNA (RAPD) markers for biodiversity measure of wild mushroom species of the Northwest mountainous region of Greece. Data mining of similarity matrices from RAPD analysis was used to extract measurable entropy parameters for mushroom biodiversity monitoring based on Shannon’s information entropy. Shannon information index provides an easy assessment of the entropy of the genetic information of the germplasm per mushroom species while the total equitability index (E<sub>H</sub>) = 0.871 offers an overall estimation of the genetic variation evenness of all species in the population of the studied mushrooms. Application of RAPDs with parallel entropy analysis is an easily applicable and low-cost valuable technology in environmental monitoring, using genetic information of wild mushroom species as an indicator that can lead to future actions in biodiversity maintenance and germplasm protection. The provided methodology can serve as a pilot procedure enriched with other environmental factors to monitor and protect wild mushroom communities native to the Greek countryside or in any part of the world and provide comparable results about biodiversity from different regions using common entropy indices.
基金National Natural Science Foundation of China, No.41171177
文摘Two typical provincial capitals （Nanjing and Zhengzhou） and two counties （Rugao and Yuanyang） in east （Jiangsu Province） and central （Henan Province） China were chosen respectively as the developed and less developed comparative cases for pedodiversity and land use diversity correlative analysis by borrowing the recently better developed pedodiversity methodology. Land use classification was worked out using remote sensing images in three different periods （1986-1988, 2000-2001 and 2004-2006） for these studied case areas before the calculation of the constituent diversity index and spatial distribution diversity index modified after Shannon entropy in 2 kmx2 km grid scale of the soil and land use pattern were conducted and then a connection index was proposed to evaluate the relationship between soil and land use diversity. Results show that during the years from 1986 to 2006, the composition and spatial distribution of regional land use pattern had changed greatly. The agricultural land area of all the studied case areas decreased obviously in which Nanjing has the highest decrement of 895.98 km2 mainly into urban use while the other land use type area changes show the same trend. The connection index of four typical soil family types and typical urban land use types, i.e., urban construction land, transportation land and industrial and mining area all increased in this period. In the studied case areas, there is the highest soil constituent diversity in Zhengzhou at 0.779 while the simplest soil constituent diversity in Rugao at 0.582. Meanwhile we have higher land use diversity in the more urbanized Jiangsu Province than Henan Province, Nanjing is ranking the first that has been getting higher and higher in the three periods at 0.366 in 1986-1988, 0.483 in 2000-2001 and 0.545 in 2004-2006. Finally, the connection index figures to evaluate the relationship between soil and land use diversity of the studied areas were compared to show the similar phenomenon that this figure grows fastest in N
文摘In recent years we extended Shannon static statistical information theory to dynamic processes and established a Shannon dynamic statistical information theory, whose core is the evolution law of dynamic entropy and dynamic information. We also proposed a corresponding Boltzmman dynamic statistical information theory. Based on the fact that the state variable evolution equation of respective dynamic systems, i.e. Fok- ker-Planck equation and Liouville diffusion equation can be regarded as their information symbol evolution equation, we derived the nonlinear evolution equations of Shannon dy- namic entropy density and dynamic information density and the nonlinear evolution equa- tions of Boltzmann dynamic entropy density and dynamic information density, that de- scribe respectively the evolution law of dynamic entropy and dynamic information. The evolution equations of these two kinds of dynamic entropies and dynamic informations show in unison that the time rate of change of dynamic entropy densities is caused by their drift, diffusion and production in state variable space inside the systems and coordinate space in the transmission processes; and that the time rate of change of dynamic infor- mation densities originates from their drift, diffusion and dissipation in state variable space inside the systems and coordinate space in the transmission processes. Entropy and in- formation have been combined with the state and its law of motion of the systems. Fur- thermore we presented the formulas of two kinds of entropy production rates and infor- mation dissipation rates, the expressions of two kinds of drift information flows and diffu- sion information flows. We proved that two kinds of information dissipation rates (or the decrease rates of the total information) were equal to their corresponding entropy produc- tion rates (or the increase rates of the total entropy) in the same dynamic system. We obtained the formulas of two kinds of dynamic mutual informations and dynamic channel capacities reflecting the dynam
