Porous materials present significant advantages for absorbing radioactive isotopes in nuclear waste streams.To improve absorption efficiency in nuclear waste treatment,a thorough understanding of the diffusion-advecti...Porous materials present significant advantages for absorbing radioactive isotopes in nuclear waste streams.To improve absorption efficiency in nuclear waste treatment,a thorough understanding of the diffusion-advection process within porous structures is essential for material design.In this study,we present advancements in the volumetric lattice Boltzmann method(VLBM)for modeling and simulating pore-scale diffusion-advection of radioactive isotopes within geopolymer porous structures.These structures are created using the phase field method(PFM)to precisely control pore architectures.In our VLBM approach,we introduce a concentration field of an isotope seamlessly coupled with the velocity field and solve it by the time evolution of its particle population function.To address the computational intensity inherent in the coupled lattice Boltzmann equations for velocity and concentration fields,we implement graphics processing unit(GPU)parallelization.Validation of the developed model involves examining the flow and diffusion fields in porous structures.Remarkably,good agreement is observed for both the velocity field from VLBM and multiphysics object-oriented simulation environment(MOOSE),and the concentration field from VLBM and the finite difference method(FDM).Furthermore,we investigate the effects of background flow,species diffusivity,and porosity on the diffusion-advection behavior by varying the background flow velocity,diffusion coefficient,and pore volume fraction,respectively.Notably,all three parameters exert an influence on the diffusion-advection process.Increased background flow and diffusivity markedly accelerate the process due to increased advection intensity and enhanced diffusion capability,respectively.Conversely,increasing the porosity has a less significant effect,causing a slight slowdown of the diffusion-advection process due to the expanded pore volume.This comprehensive parametric study provides valuable insights into the kinetics of isotope uptake in porous structures,facilitating the development of porous materials for nuclear waste treatment applications.展开更多
In this study,the vertical components of broadband teleseismic P wave data recorded by China Earthquake Network are used to image the rupture processes of the February 6th,2023 Turkish earthquake doublet via back proj...In this study,the vertical components of broadband teleseismic P wave data recorded by China Earthquake Network are used to image the rupture processes of the February 6th,2023 Turkish earthquake doublet via back projection analysis.Data in two frequency bands(0.5-2 Hz and 1-3 Hz)are used in the imaging processes.The results show that the rupture of the first event extends about 200 km to the northeast and about 150 km to the southwest,lasting~90 s in total.The southwestern rupture is triggered by the northeastern rupture,demonstrating a sequential bidirectional unilateral rupture pattern.The rupture of the second event extends approximately 80 km in both northeast and west directions,lasting~35 s in total and demonstrates a typical bilateral rupture feature.The cascading ruptures on both sides also reflect the occurrence of selective rupture behaviors on bifurcated faults.In addition,we observe super-shear ruptures on certain fault sections with relatively straight fault structures and sparse aftershocks.展开更多
To equip data-driven dynamic chemical process models with strong interpretability,we develop a light attention–convolution–gate recurrent unit(LACG)architecture with three sub-modules—a basic module,a brand-new lig...To equip data-driven dynamic chemical process models with strong interpretability,we develop a light attention–convolution–gate recurrent unit(LACG)architecture with three sub-modules—a basic module,a brand-new light attention module,and a residue module—that are specially designed to learn the general dynamic behavior,transient disturbances,and other input factors of chemical processes,respectively.Combined with a hyperparameter optimization framework,Optuna,the effectiveness of the proposed LACG is tested by distributed control system data-driven modeling experiments on the discharge flowrate of an actual deethanization process.The LACG model provides significant advantages in prediction accuracy and model generalization compared with other models,including the feedforward neural network,convolution neural network,long short-term memory(LSTM),and attention-LSTM.Moreover,compared with the simulation results of a deethanization model built using Aspen Plus Dynamics V12.1,the LACG parameters are demonstrated to be interpretable,and more details on the variable interactions can be observed from the model parameters in comparison with the traditional interpretable model attention-LSTM.This contribution enriches interpretable machine learning knowledge and provides a reliable method with high accuracy for actual chemical process modeling,paving a route to intelligent manufacturing.展开更多
This study investigated the correlations between mechanical properties and mineralogy of granite using the digital image processing(DIP) and discrete element method(DEM). The results showed that the X-ray diffraction(...This study investigated the correlations between mechanical properties and mineralogy of granite using the digital image processing(DIP) and discrete element method(DEM). The results showed that the X-ray diffraction(XRD)-based DIP method effectively analyzed the mineral composition contents and spatial distributions of granite. During the particle flow code(PFC2D) model calibration phase, the numerical simulation exhibited that the uniaxial compressive strength(UCS) value, elastic modulus(E), and failure pattern of the granite specimen in the UCS test were comparable to the experiment. By establishing 351 sets of numerical models and exploring the impacts of mineral composition on the mechanical properties of granite, it indicated that there was no negative correlation between quartz and feldspar for UCS, tensile strength(σ_(t)), and E. In contrast, mica had a significant negative correlation for UCS, σ_(t), and E. The presence of quartz increased the brittleness of granite, whereas the presence of mica and feldspar increased its ductility in UCS and direct tensile strength(DTS) tests. Varying contents of major mineral compositions in granite showed minor influence on the number of cracks in both UCS and DTS tests.展开更多
Attitude is one of the crucial parameters for space objects and plays a vital role in collision prediction and debris removal.Analyzing light curves to determine attitude is the most commonly used method.In photometri...Attitude is one of the crucial parameters for space objects and plays a vital role in collision prediction and debris removal.Analyzing light curves to determine attitude is the most commonly used method.In photometric observations,outliers may exist in the obtained light curves due to various reasons.Therefore,preprocessing is required to remove these outliers to obtain high quality light curves.Through statistical analysis,the reasons leading to outliers can be categorized into two main types:first,the brightness of the object significantly increases due to the passage of a star nearby,referred to as“stellar contamination,”and second,the brightness markedly decreases due to cloudy cover,referred to as“cloudy contamination.”The traditional approach of manually inspecting images for contamination is time-consuming and labor-intensive.However,we propose the utilization of machine learning methods as a substitute.Convolutional Neural Networks and SVMs are employed to identify cases of stellar contamination and cloudy contamination,achieving F1 scores of 1.00 and 0.98 on a test set,respectively.We also explore other machine learning methods such as ResNet-18 and Light Gradient Boosting Machine,then conduct comparative analyses of the results.展开更多
The tropomyosin(TM)fractions of crab protems may cause allergic reactions in mdividuals susceptible to allergies;however,efficient and safe methods by which to reduce such allergenicity are not currently available.The...The tropomyosin(TM)fractions of crab protems may cause allergic reactions in mdividuals susceptible to allergies;however,efficient and safe methods by which to reduce such allergenicity are not currently available.Therefore,in this study,the effects of three different processing methods,i.e.,microwave,ultrasound,and high temperature-pressure(HTP)treatments,on the digestion stability of TM from Chinese mitten crab muscle and the allergenicity of TM digestion products were explored.sodium dodecyl sulfate-polyacrylamide gel electrophoresis analysis showed that microwaving had little effect on the digestion stability of TM.In contrast,ultrasound and HTP treatments facilitated the degradation of TM.Similarly,Western blotting and inhibition ELISA indicated that the IgE-binding activity of TM was significantly reduced after treatment with ultrasound or HTP.Among the three different proces sing methods,HTP was the most effective method for improving digestibility of TM and reducing immunoreactivity.This finding provides new insights into treatments for crab allergies.展开更多
The current velocity observation of LADCP(Lowered Acoustic Doppler Current Profiler)has the advantages of a large vertical range of observation and high operability compared with traditional current measurement method...The current velocity observation of LADCP(Lowered Acoustic Doppler Current Profiler)has the advantages of a large vertical range of observation and high operability compared with traditional current measurement methods,and is being widely used in the field of ocean observation.Shear and inverse methods are now commonly used by the international marine community to process LADCP data and calculate ocean current profiles.The two methods have their advantages and shortcomings.The shear method calculates the value of current shear more accurately,while the accuracy in an absolute value of the current is lower.The inverse method calculates the absolute value of the current velocity more accurately,but the current shear is less accurate.Based on the shear method,this paper proposes a layering shear method to calculate the current velocity profile by“layering averaging”,and proposes corresponding current calculation methods according to the different types of problems in several field observation data from the western Pacific,forming an independent LADCP data processing system.The comparison results have shown that the layering shear method can achieve the same effect as the inverse method in the calculation of the absolute value of current velocity,while retaining the advantages of the shear method in the calculation of a value of the current shear.展开更多
In the graph signal processing(GSP)framework,distributed algorithms are highly desirable in processing signals defined on large-scale networks.However,in most existing distributed algorithms,all nodes homogeneously pe...In the graph signal processing(GSP)framework,distributed algorithms are highly desirable in processing signals defined on large-scale networks.However,in most existing distributed algorithms,all nodes homogeneously perform the local computation,which calls for heavy computational and communication costs.Moreover,in many real-world networks,such as those with straggling nodes,the homogeneous manner may result in serious delay or even failure.To this end,we propose active network decomposition algorithms to select non-straggling nodes(normal nodes)that perform the main computation and communication across the network.To accommodate the decomposition in different kinds of networks,two different approaches are developed,one is centralized decomposition that leverages the adjacency of the network and the other is distributed decomposition that employs the indicator message transmission between neighboring nodes,which constitutes the main contribution of this paper.By incorporating the active decomposition scheme,a distributed Newton method is employed to solve the least squares problem in GSP,where the Hessian inverse is approximately evaluated by patching a series of inverses of local Hessian matrices each of which is governed by one normal node.The proposed algorithm inherits the fast convergence of the second-order algorithms while maintains low computational and communication cost.Numerical examples demonstrate the effectiveness of the proposed algorithm.展开更多
The radio-occultation observations taken by Tianwen-1 are aiming to study the properties of solar wind.A new method of frequency fluctuation(FF)estimation is presented for processing the down-link signals of Tianwen-1...The radio-occultation observations taken by Tianwen-1 are aiming to study the properties of solar wind.A new method of frequency fluctuation(FF)estimation is presented for processing the down-link signals of Tianwen-1 during the occultation period to study the properties of the coronal plasma at the heliocentric distances of 4.48–19 R_(⊙).Because of low S/N as well as the phase fluctuation phenomena caused by solar activity,a Kalman based on polynomial prediction methods is proposed to avoid the phase locked loop loss lock.A new detrend method based on multi-level iteration correction is proposed to estimate Doppler shift to get more accurate power density spectra of FF in the low frequency region.The data analyze procedure is used to get the properties of the solar corona during the occultation.The method was finally verified at the point when the solar offset is 5.7 R_(⊙),frequency tracking was successfully performed on data with a carrier-to-noise ratio of about 28 dBHz.The density spectra obtained by the improved method are basically the same when the frequency is greater than 2 mHz,the uncertainty in the result of the rms of the FF obtained by removing the trend term with different order polynomials is less than 3.3%.The data without eliminating interference show a large error for different detrending orders,which justifies the need for an improved approach.Finally,the frequency fluctuation results combined with the information on intensity fluctuation obtained by the new method are compared with the results of the integrated Space Weather Analysis system and theoretical formula,which verifies that the processing results in this paper have a certain degree of credibility.展开更多
Background: Cassava tuber crop is a staple food rich in carbohydrates and utilized in various forms by millions of Nigerians. The storage root of the cassava contains linamarin, a cyanogenic glycoside that is easily h...Background: Cassava tuber crop is a staple food rich in carbohydrates and utilized in various forms by millions of Nigerians. The storage root of the cassava contains linamarin, a cyanogenic glycoside that is easily hydrolyzed to release cyanide salt compounds which is toxic to the nervous system especially the optic nerve, sometimes leading to optic neuropathy and visual impairment. Aim: The aim of this study is to find out the impact of selected processing methods of high-level cyanide in cassava on optic neuropathy in Wistar albino rats. Methodology: Twenty-four Wistar albino rats were fed with different concentration and duration of predetermined high-cyanide content cassava root cultivar which was processed using different processing methods adopted by various communities in Rivers State, Nigeria (for human consumption). A control group of 3 Wistar albino rats was fed with normal “Growth Mesh” meals. The pre and post weights of the animals and the fundoscopic optic nerve status of the rats were evaluated after 30 and 60 days. SPSS Version 25 was employed for descriptive and inferential statistical analyses. A p-value of ≤0.05 was considered statistically significant. Results: The Cassava species available in Rivers State have high cyanide content (2336.79 mg CN<sup>-</sup>/kg dry weight of cassava). There was statistically significant reduction in the cyanide content (p = 0.000) depending on the various common processing methods (into garri for human consumption): 24 hours, 48 hours, fermentation;with and without red palm oil additive. The individual weights as well as the mean weight of the 24 rats in the experimental group increased gradually from the first week to the 9<sup>th</sup> week with a slight weight reduction on the third and fourth weeks which was not statistically significant (p = 0.092). However, there was a steady increase in the weights of the animals in the control group throughout the 9 weeks. Varying degrees of optic neuropathy occurred, worse with the rats that had 24-hour fermented cassava twice daily for 60 days. The intra and inter group differences in the optic disc changes was statistically significant (p = 0.000). Conclusion: Longer duration of processing cassava roots into garri for human consumption reduces its cyanide content and minimizes the adverse impact on the optic nerve.展开更多
Geological radar probing technology finds wide application in engineering projects. The high-precision characteristics of geologic radar should be studied in connection with fine processing and interpretation. This ar...Geological radar probing technology finds wide application in engineering projects. The high-precision characteristics of geologic radar should be studied in connection with fine processing and interpretation. This article discusses such issues as (1) geologic radar noise source and (2) fine processing and interpretation of radar data. It is focused on how to achieve fine processing and interpretation.展开更多
Nowadays, it becomes very urgent to find remain oil under the oil shortage worldwide.However, most of simple reservoirs have been discovered and those undiscovered are mostly complex structural, stratigraphic and lith...Nowadays, it becomes very urgent to find remain oil under the oil shortage worldwide.However, most of simple reservoirs have been discovered and those undiscovered are mostly complex structural, stratigraphic and lithologic ones. Summarized in this paper is the integrated seismic processing/interpretation technique established on the basis of pre-stack AVO processing and interpretation.Information feedbacks occurred between the pre-stack and post-stack processes so as to improve the accuracy in utilization of data and avoid pitfalls in seismic attributes. Through the integration of seismic data with geologic data, parameters that were most essential to describing hydrocarbon characteristics were determined and comprehensively appraised, and regularities of reservoir generation and distribution were described so as to accurately appraise reservoirs, delineate favorite traps and pinpoint wells.展开更多
Branching river channels and the coexistence of valleys, ridges, hiils, and slopes＇as the result of long-term weathering and erosion form the unique loess topography. The Changqing Geophysical Company, working in the...Branching river channels and the coexistence of valleys, ridges, hiils, and slopes＇as the result of long-term weathering and erosion form the unique loess topography. The Changqing Geophysical Company, working in these complex conditions, has established a suite of technologies for high-fidelity processing and fine interpretation of seismic data. This article introduces the processes involved in the data processing and interpretation and illustrates the results.展开更多
Difficulty discrimination is an important step in autonomous design and interpreting teaching materials development, which is related to scientifi c nature of the materials, teaching effectiveness, and sequential teac...Difficulty discrimination is an important step in autonomous design and interpreting teaching materials development, which is related to scientifi c nature of the materials, teaching effectiveness, and sequential teaching progress. In this paper, we focus on the diffi culty discrimination of interpretation teaching materials on the basis of analytic hierarchy process and natural language processing. We analyze several factors which affect interpretation teaching materials, and we introduce theories of analytic hierarchy process and natural language processing which is intuitive and credible operation basis.展开更多
Processing method is one of the maln factors affecting the quality of hon-eysuckIe herbs, which is directIy reIated to economic benefits of farmers. This paper compares various processing methods of honeysuckIe to pro...Processing method is one of the maln factors affecting the quality of hon-eysuckIe herbs, which is directIy reIated to economic benefits of farmers. This paper compares various processing methods of honeysuckIe to provide some references for deveIoping a suitabIe processing procedure that can be used in Iarge-scale pro-duction and improve herb quality.展开更多
A comprehensive understanding of spatial distribution and clustering patterns of gravels is of great significance for ecological restoration and monitoring.However,traditional methods for studying gravels are low-effi...A comprehensive understanding of spatial distribution and clustering patterns of gravels is of great significance for ecological restoration and monitoring.However,traditional methods for studying gravels are low-efficiency and have many errors.This study researched the spatial distribution and cluster characteristics of gravels based on digital image processing technology combined with a self-organizing map(SOM)and multivariate statistical methods in the grassland of northern Tibetan Plateau.Moreover,the correlation of morphological parameters of gravels between different cluster groups and the environmental factors affecting gravel distribution were analyzed.The results showed that the morphological characteristics of gravels in northern region(cluster C)and southern region(cluster B)of the Tibetan Plateau were similar,with a low gravel coverage,small gravel diameter,and elongated shape.These regions were mainly distributed in high mountainous areas with large topographic relief.The central region(cluster A)has high coverage of gravels with a larger diameter,mainly distributed in high-altitude plains with smaller undulation.Principal component analysis(PCA)results showed that the gravel distribution of cluster A may be mainly affected by vegetation,while those in clusters B and C could be mainly affected by topography,climate,and soil.The study confirmed that the combination of digital image processing technology and SOM could effectively analyzed the spatial distribution characteristics of gravels,providing a new mode for gravel research.展开更多
In the existing landslide susceptibility prediction(LSP)models,the influences of random errors in landslide conditioning factors on LSP are not considered,instead the original conditioning factors are directly taken a...In the existing landslide susceptibility prediction(LSP)models,the influences of random errors in landslide conditioning factors on LSP are not considered,instead the original conditioning factors are directly taken as the model inputs,which brings uncertainties to LSP results.This study aims to reveal the influence rules of the different proportional random errors in conditioning factors on the LSP un-certainties,and further explore a method which can effectively reduce the random errors in conditioning factors.The original conditioning factors are firstly used to construct original factors-based LSP models,and then different random errors of 5%,10%,15% and 20%are added to these original factors for con-structing relevant errors-based LSP models.Secondly,low-pass filter-based LSP models are constructed by eliminating the random errors using low-pass filter method.Thirdly,the Ruijin County of China with 370 landslides and 16 conditioning factors are used as study case.Three typical machine learning models,i.e.multilayer perceptron(MLP),support vector machine(SVM)and random forest(RF),are selected as LSP models.Finally,the LSP uncertainties are discussed and results show that:(1)The low-pass filter can effectively reduce the random errors in conditioning factors to decrease the LSP uncertainties.(2)With the proportions of random errors increasing from 5%to 20%,the LSP uncertainty increases continuously.(3)The original factors-based models are feasible for LSP in the absence of more accurate conditioning factors.(4)The influence degrees of two uncertainty issues,machine learning models and different proportions of random errors,on the LSP modeling are large and basically the same.(5)The Shapley values effectively explain the internal mechanism of machine learning model predicting landslide sus-ceptibility.In conclusion,greater proportion of random errors in conditioning factors results in higher LSP uncertainty,and low-pass filter can effectively reduce these random errors.展开更多
In modern transportation,pavement is one of the most important civil infrastructures for the movement of vehicles and pedestrians.Pavement service quality and service life are of great importance for civil engineers a...In modern transportation,pavement is one of the most important civil infrastructures for the movement of vehicles and pedestrians.Pavement service quality and service life are of great importance for civil engineers as they directly affect the regular service for the users.Therefore,monitoring the health status of pavement before irreversible damage occurs is essential for timely maintenance,which in turn ensures public transportation safety.Many pavement damages can be detected and analyzed by monitoring the structure dynamic responses and evaluating road surface conditions.Advanced technologies can be employed for the collection and analysis of such data,including various intrusive sensing techniques,image processing techniques,and machine learning methods.This review summarizes the state-ofthe-art of these three technologies in pavement engineering in recent years and suggests possible developments for future pavement monitoring and analysis based on these approaches.展开更多
General purpose graphic processing unit （GPU） calculation technology is gradually widely used in various fields. Its mode of single instruction, multiple threads is capable of seismic numerical simulation which has ...General purpose graphic processing unit （GPU） calculation technology is gradually widely used in various fields. Its mode of single instruction, multiple threads is capable of seismic numerical simulation which has a huge quantity of data and calculation steps. In this study, we introduce a GPU-based parallel calculation method of a precise integration method （PIM） for seismic forward modeling. Compared with CPU single-core calculation, GPU parallel calculating perfectly keeps the features of PIM, which has small bandwidth, high accuracy and capability of modeling complex substructures, and GPU calculation brings high computational efficiency, which means that high-performing GPU parallel calculation can make seismic forward modeling closer to real seismic records.展开更多
Faba bean(Vicia faba L.)has been identified as a rich source of L-DOPA,which is used in treating Parkinson's disease.Biosynthesis and accumulation of active substances such as L-DOPA in plant tissues may interact ...Faba bean(Vicia faba L.)has been identified as a rich source of L-DOPA,which is used in treating Parkinson's disease.Biosynthesis and accumulation of active substances such as L-DOPA in plant tissues may interact with growing conditions and processing methods.Accumulation trends of L-DOPA in various faba bean organs and the effect of drought stress and N fertilization on L-DOPA content were studied in a field and two greenhouse experiments.The influence of various processing methods on L-DOPA content of faba bean tissues was evaluated.The highest L-DOPA content was detected in fresh leaves(22.4 mg g^(-1))followed by flowers,young pods,mature seeds,and roots.Regardless of processing method,L-DOPA concentration in faba bean tissues was significantly reduced when tissues were boiled or dried.Among various methods of processing,freezing had the lowest detrimental effect,reducing L-DOPA concentrations by 24.1%and 21.1%in leaves and seeds,respectively.Drought stress elevated L-DOPA concentration,and maximum L-DOPA(23.3 mg g^(-1)of biomass)was extracted from plants grown under severe drought stress.However,L-DOPA yield(L-DOPA concentration×biomass)was compromised,owing to the adverse influence of drought stress on dry matter production.No significant difference in L-DOPA concentration was detected among various N application rates.展开更多
基金supported as part of the Center for Hierarchical Waste Form Materials,an Energy Frontier Research Center funded by the U.S.Department of Energy,Office of Science,Basic Energy Sciences under Award No.DE-SC0016574.
文摘Porous materials present significant advantages for absorbing radioactive isotopes in nuclear waste streams.To improve absorption efficiency in nuclear waste treatment,a thorough understanding of the diffusion-advection process within porous structures is essential for material design.In this study,we present advancements in the volumetric lattice Boltzmann method(VLBM)for modeling and simulating pore-scale diffusion-advection of radioactive isotopes within geopolymer porous structures.These structures are created using the phase field method(PFM)to precisely control pore architectures.In our VLBM approach,we introduce a concentration field of an isotope seamlessly coupled with the velocity field and solve it by the time evolution of its particle population function.To address the computational intensity inherent in the coupled lattice Boltzmann equations for velocity and concentration fields,we implement graphics processing unit(GPU)parallelization.Validation of the developed model involves examining the flow and diffusion fields in porous structures.Remarkably,good agreement is observed for both the velocity field from VLBM and multiphysics object-oriented simulation environment(MOOSE),and the concentration field from VLBM and the finite difference method(FDM).Furthermore,we investigate the effects of background flow,species diffusivity,and porosity on the diffusion-advection behavior by varying the background flow velocity,diffusion coefficient,and pore volume fraction,respectively.Notably,all three parameters exert an influence on the diffusion-advection process.Increased background flow and diffusivity markedly accelerate the process due to increased advection intensity and enhanced diffusion capability,respectively.Conversely,increasing the porosity has a less significant effect,causing a slight slowdown of the diffusion-advection process due to the expanded pore volume.This comprehensive parametric study provides valuable insights into the kinetics of isotope uptake in porous structures,facilitating the development of porous materials for nuclear waste treatment applications.
基金supported by the National Key R&D Program of China(No.2022YFF0800601)National Scientific Foundation of China(Nos.41930103 and 41774047).
文摘In this study,the vertical components of broadband teleseismic P wave data recorded by China Earthquake Network are used to image the rupture processes of the February 6th,2023 Turkish earthquake doublet via back projection analysis.Data in two frequency bands(0.5-2 Hz and 1-3 Hz)are used in the imaging processes.The results show that the rupture of the first event extends about 200 km to the northeast and about 150 km to the southwest,lasting~90 s in total.The southwestern rupture is triggered by the northeastern rupture,demonstrating a sequential bidirectional unilateral rupture pattern.The rupture of the second event extends approximately 80 km in both northeast and west directions,lasting~35 s in total and demonstrates a typical bilateral rupture feature.The cascading ruptures on both sides also reflect the occurrence of selective rupture behaviors on bifurcated faults.In addition,we observe super-shear ruptures on certain fault sections with relatively straight fault structures and sparse aftershocks.
基金support provided by the National Natural Science Foundation of China(22122802,22278044,and 21878028)the Chongqing Science Fund for Distinguished Young Scholars(CSTB2022NSCQ-JQX0021)the Fundamental Research Funds for the Central Universities(2022CDJXY-003).
文摘To equip data-driven dynamic chemical process models with strong interpretability,we develop a light attention–convolution–gate recurrent unit(LACG)architecture with three sub-modules—a basic module,a brand-new light attention module,and a residue module—that are specially designed to learn the general dynamic behavior,transient disturbances,and other input factors of chemical processes,respectively.Combined with a hyperparameter optimization framework,Optuna,the effectiveness of the proposed LACG is tested by distributed control system data-driven modeling experiments on the discharge flowrate of an actual deethanization process.The LACG model provides significant advantages in prediction accuracy and model generalization compared with other models,including the feedforward neural network,convolution neural network,long short-term memory(LSTM),and attention-LSTM.Moreover,compared with the simulation results of a deethanization model built using Aspen Plus Dynamics V12.1,the LACG parameters are demonstrated to be interpretable,and more details on the variable interactions can be observed from the model parameters in comparison with the traditional interpretable model attention-LSTM.This contribution enriches interpretable machine learning knowledge and provides a reliable method with high accuracy for actual chemical process modeling,paving a route to intelligent manufacturing.
基金This research was supported by the Department of Mining Engineering at the University of Utah.In addition,the lead author wishes to acknowledge the financial support received from the Talent Introduction Project,part of the Elite Program of Shandong University of Science and Technology(No.0104060540171).
文摘This study investigated the correlations between mechanical properties and mineralogy of granite using the digital image processing(DIP) and discrete element method(DEM). The results showed that the X-ray diffraction(XRD)-based DIP method effectively analyzed the mineral composition contents and spatial distributions of granite. During the particle flow code(PFC2D) model calibration phase, the numerical simulation exhibited that the uniaxial compressive strength(UCS) value, elastic modulus(E), and failure pattern of the granite specimen in the UCS test were comparable to the experiment. By establishing 351 sets of numerical models and exploring the impacts of mineral composition on the mechanical properties of granite, it indicated that there was no negative correlation between quartz and feldspar for UCS, tensile strength(σ_(t)), and E. In contrast, mica had a significant negative correlation for UCS, σ_(t), and E. The presence of quartz increased the brittleness of granite, whereas the presence of mica and feldspar increased its ductility in UCS and direct tensile strength(DTS) tests. Varying contents of major mineral compositions in granite showed minor influence on the number of cracks in both UCS and DTS tests.
基金funded by the National Natural Science Foundation of China(NSFC,Nos.12373086 and 12303082)CAS“Light of West China”Program+2 种基金Yunnan Revitalization Talent Support Program in Yunnan ProvinceNational Key R&D Program of ChinaGravitational Wave Detection Project No.2022YFC2203800。
文摘Attitude is one of the crucial parameters for space objects and plays a vital role in collision prediction and debris removal.Analyzing light curves to determine attitude is the most commonly used method.In photometric observations,outliers may exist in the obtained light curves due to various reasons.Therefore,preprocessing is required to remove these outliers to obtain high quality light curves.Through statistical analysis,the reasons leading to outliers can be categorized into two main types:first,the brightness of the object significantly increases due to the passage of a star nearby,referred to as“stellar contamination,”and second,the brightness markedly decreases due to cloudy cover,referred to as“cloudy contamination.”The traditional approach of manually inspecting images for contamination is time-consuming and labor-intensive.However,we propose the utilization of machine learning methods as a substitute.Convolutional Neural Networks and SVMs are employed to identify cases of stellar contamination and cloudy contamination,achieving F1 scores of 1.00 and 0.98 on a test set,respectively.We also explore other machine learning methods such as ResNet-18 and Light Gradient Boosting Machine,then conduct comparative analyses of the results.
基金supported by the earmarked fund for the Anhui Provincial Modern Agri-industry Technology Research System(AHCYJSTX-08)the China Agriculture Research System of MOF and MARA(CARS-48)。
文摘The tropomyosin(TM)fractions of crab protems may cause allergic reactions in mdividuals susceptible to allergies;however,efficient and safe methods by which to reduce such allergenicity are not currently available.Therefore,in this study,the effects of three different processing methods,i.e.,microwave,ultrasound,and high temperature-pressure(HTP)treatments,on the digestion stability of TM from Chinese mitten crab muscle and the allergenicity of TM digestion products were explored.sodium dodecyl sulfate-polyacrylamide gel electrophoresis analysis showed that microwaving had little effect on the digestion stability of TM.In contrast,ultrasound and HTP treatments facilitated the degradation of TM.Similarly,Western blotting and inhibition ELISA indicated that the IgE-binding activity of TM was significantly reduced after treatment with ultrasound or HTP.Among the three different proces sing methods,HTP was the most effective method for improving digestibility of TM and reducing immunoreactivity.This finding provides new insights into treatments for crab allergies.
基金The National Natural Science Foundation of China under contract No.42206033the Marine Geological Survey Program of China Geological Survey under contract No.DD20221706+1 种基金the Research Foundation of National Engineering Research Center for Gas Hydrate Exploration and Development,Innovation Team Project,under contract No.2022GMGSCXYF41003the Scientific Research Fund of the Second Institute of Oceanography,Ministry of Natural Resources,under contract No.JG2006.
文摘The current velocity observation of LADCP(Lowered Acoustic Doppler Current Profiler)has the advantages of a large vertical range of observation and high operability compared with traditional current measurement methods,and is being widely used in the field of ocean observation.Shear and inverse methods are now commonly used by the international marine community to process LADCP data and calculate ocean current profiles.The two methods have their advantages and shortcomings.The shear method calculates the value of current shear more accurately,while the accuracy in an absolute value of the current is lower.The inverse method calculates the absolute value of the current velocity more accurately,but the current shear is less accurate.Based on the shear method,this paper proposes a layering shear method to calculate the current velocity profile by“layering averaging”,and proposes corresponding current calculation methods according to the different types of problems in several field observation data from the western Pacific,forming an independent LADCP data processing system.The comparison results have shown that the layering shear method can achieve the same effect as the inverse method in the calculation of the absolute value of current velocity,while retaining the advantages of the shear method in the calculation of a value of the current shear.
基金supported by National Natural Science Foundation of China(Grant No.61761011)Natural Science Foundation of Guangxi(Grant No.2020GXNSFBA297078).
文摘In the graph signal processing(GSP)framework,distributed algorithms are highly desirable in processing signals defined on large-scale networks.However,in most existing distributed algorithms,all nodes homogeneously perform the local computation,which calls for heavy computational and communication costs.Moreover,in many real-world networks,such as those with straggling nodes,the homogeneous manner may result in serious delay or even failure.To this end,we propose active network decomposition algorithms to select non-straggling nodes(normal nodes)that perform the main computation and communication across the network.To accommodate the decomposition in different kinds of networks,two different approaches are developed,one is centralized decomposition that leverages the adjacency of the network and the other is distributed decomposition that employs the indicator message transmission between neighboring nodes,which constitutes the main contribution of this paper.By incorporating the active decomposition scheme,a distributed Newton method is employed to solve the least squares problem in GSP,where the Hessian inverse is approximately evaluated by patching a series of inverses of local Hessian matrices each of which is governed by one normal node.The proposed algorithm inherits the fast convergence of the second-order algorithms while maintains low computational and communication cost.Numerical examples demonstrate the effectiveness of the proposed algorithm.
基金funded by the Astronomical Joint Fund of the National Natural Science Foundation of ChinaChinese Academy of Sciences(Grant Nos.U1831114,11941002,and 12073048)。
文摘The radio-occultation observations taken by Tianwen-1 are aiming to study the properties of solar wind.A new method of frequency fluctuation(FF)estimation is presented for processing the down-link signals of Tianwen-1 during the occultation period to study the properties of the coronal plasma at the heliocentric distances of 4.48–19 R_(⊙).Because of low S/N as well as the phase fluctuation phenomena caused by solar activity,a Kalman based on polynomial prediction methods is proposed to avoid the phase locked loop loss lock.A new detrend method based on multi-level iteration correction is proposed to estimate Doppler shift to get more accurate power density spectra of FF in the low frequency region.The data analyze procedure is used to get the properties of the solar corona during the occultation.The method was finally verified at the point when the solar offset is 5.7 R_(⊙),frequency tracking was successfully performed on data with a carrier-to-noise ratio of about 28 dBHz.The density spectra obtained by the improved method are basically the same when the frequency is greater than 2 mHz,the uncertainty in the result of the rms of the FF obtained by removing the trend term with different order polynomials is less than 3.3%.The data without eliminating interference show a large error for different detrending orders,which justifies the need for an improved approach.Finally,the frequency fluctuation results combined with the information on intensity fluctuation obtained by the new method are compared with the results of the integrated Space Weather Analysis system and theoretical formula,which verifies that the processing results in this paper have a certain degree of credibility.
文摘Background: Cassava tuber crop is a staple food rich in carbohydrates and utilized in various forms by millions of Nigerians. The storage root of the cassava contains linamarin, a cyanogenic glycoside that is easily hydrolyzed to release cyanide salt compounds which is toxic to the nervous system especially the optic nerve, sometimes leading to optic neuropathy and visual impairment. Aim: The aim of this study is to find out the impact of selected processing methods of high-level cyanide in cassava on optic neuropathy in Wistar albino rats. Methodology: Twenty-four Wistar albino rats were fed with different concentration and duration of predetermined high-cyanide content cassava root cultivar which was processed using different processing methods adopted by various communities in Rivers State, Nigeria (for human consumption). A control group of 3 Wistar albino rats was fed with normal “Growth Mesh” meals. The pre and post weights of the animals and the fundoscopic optic nerve status of the rats were evaluated after 30 and 60 days. SPSS Version 25 was employed for descriptive and inferential statistical analyses. A p-value of ≤0.05 was considered statistically significant. Results: The Cassava species available in Rivers State have high cyanide content (2336.79 mg CN<sup>-</sup>/kg dry weight of cassava). There was statistically significant reduction in the cyanide content (p = 0.000) depending on the various common processing methods (into garri for human consumption): 24 hours, 48 hours, fermentation;with and without red palm oil additive. The individual weights as well as the mean weight of the 24 rats in the experimental group increased gradually from the first week to the 9<sup>th</sup> week with a slight weight reduction on the third and fourth weeks which was not statistically significant (p = 0.092). However, there was a steady increase in the weights of the animals in the control group throughout the 9 weeks. Varying degrees of optic neuropathy occurred, worse with the rats that had 24-hour fermented cassava twice daily for 60 days. The intra and inter group differences in the optic disc changes was statistically significant (p = 0.000). Conclusion: Longer duration of processing cassava roots into garri for human consumption reduces its cyanide content and minimizes the adverse impact on the optic nerve.
基金This project is sponsored by The Special Fund of Scientific Instruments of National Natural Science Foundation of China(50127402) and The Geophysical Responses to The High-resolution Exploration for Coal-methane of 973 Program(2002CB211707).
文摘Geological radar probing technology finds wide application in engineering projects. The high-precision characteristics of geologic radar should be studied in connection with fine processing and interpretation. This article discusses such issues as (1) geologic radar noise source and (2) fine processing and interpretation of radar data. It is focused on how to achieve fine processing and interpretation.
文摘Nowadays, it becomes very urgent to find remain oil under the oil shortage worldwide.However, most of simple reservoirs have been discovered and those undiscovered are mostly complex structural, stratigraphic and lithologic ones. Summarized in this paper is the integrated seismic processing/interpretation technique established on the basis of pre-stack AVO processing and interpretation.Information feedbacks occurred between the pre-stack and post-stack processes so as to improve the accuracy in utilization of data and avoid pitfalls in seismic attributes. Through the integration of seismic data with geologic data, parameters that were most essential to describing hydrocarbon characteristics were determined and comprehensively appraised, and regularities of reservoir generation and distribution were described so as to accurately appraise reservoirs, delineate favorite traps and pinpoint wells.
文摘Branching river channels and the coexistence of valleys, ridges, hiils, and slopes＇as the result of long-term weathering and erosion form the unique loess topography. The Changqing Geophysical Company, working in these complex conditions, has established a suite of technologies for high-fidelity processing and fine interpretation of seismic data. This article introduces the processes involved in the data processing and interpretation and illustrates the results.
文摘Difficulty discrimination is an important step in autonomous design and interpreting teaching materials development, which is related to scientifi c nature of the materials, teaching effectiveness, and sequential teaching progress. In this paper, we focus on the diffi culty discrimination of interpretation teaching materials on the basis of analytic hierarchy process and natural language processing. We analyze several factors which affect interpretation teaching materials, and we introduce theories of analytic hierarchy process and natural language processing which is intuitive and credible operation basis.
基金Supported by National Key Technology Research and Development Program during the12thFive-Year Plan Period(2011BAI06B01,2011BAC02B04)Special Fund for Traditional Chinese Medicine Scientific Research(201407002)+1 种基金Science and Technology Development Program of Shandong Province(2014GSF119018)Traditional Chinese Medicine Science and Technology Development Program of Shandong Province(2011Z-003-2)~~
文摘Processing method is one of the maln factors affecting the quality of hon-eysuckIe herbs, which is directIy reIated to economic benefits of farmers. This paper compares various processing methods of honeysuckIe to provide some references for deveIoping a suitabIe processing procedure that can be used in Iarge-scale pro-duction and improve herb quality.
基金funded by the National Natural Science Foundation of China(41971226,41871357)the Major Research and Development and Achievement Transformation Projects of Qinghai,China(2022-QY-224)the Strategic Priority Research Program of the Chinese Academy of Sciences(XDA28110502,XDA19030303).
文摘A comprehensive understanding of spatial distribution and clustering patterns of gravels is of great significance for ecological restoration and monitoring.However,traditional methods for studying gravels are low-efficiency and have many errors.This study researched the spatial distribution and cluster characteristics of gravels based on digital image processing technology combined with a self-organizing map(SOM)and multivariate statistical methods in the grassland of northern Tibetan Plateau.Moreover,the correlation of morphological parameters of gravels between different cluster groups and the environmental factors affecting gravel distribution were analyzed.The results showed that the morphological characteristics of gravels in northern region(cluster C)and southern region(cluster B)of the Tibetan Plateau were similar,with a low gravel coverage,small gravel diameter,and elongated shape.These regions were mainly distributed in high mountainous areas with large topographic relief.The central region(cluster A)has high coverage of gravels with a larger diameter,mainly distributed in high-altitude plains with smaller undulation.Principal component analysis(PCA)results showed that the gravel distribution of cluster A may be mainly affected by vegetation,while those in clusters B and C could be mainly affected by topography,climate,and soil.The study confirmed that the combination of digital image processing technology and SOM could effectively analyzed the spatial distribution characteristics of gravels,providing a new mode for gravel research.
基金This work is funded by the National Natural Science Foundation of China(Grant Nos.42377164 and 52079062)the National Science Fund for Distinguished Young Scholars of China(Grant No.52222905).
文摘In the existing landslide susceptibility prediction(LSP)models,the influences of random errors in landslide conditioning factors on LSP are not considered,instead the original conditioning factors are directly taken as the model inputs,which brings uncertainties to LSP results.This study aims to reveal the influence rules of the different proportional random errors in conditioning factors on the LSP un-certainties,and further explore a method which can effectively reduce the random errors in conditioning factors.The original conditioning factors are firstly used to construct original factors-based LSP models,and then different random errors of 5%,10%,15% and 20%are added to these original factors for con-structing relevant errors-based LSP models.Secondly,low-pass filter-based LSP models are constructed by eliminating the random errors using low-pass filter method.Thirdly,the Ruijin County of China with 370 landslides and 16 conditioning factors are used as study case.Three typical machine learning models,i.e.multilayer perceptron(MLP),support vector machine(SVM)and random forest(RF),are selected as LSP models.Finally,the LSP uncertainties are discussed and results show that:(1)The low-pass filter can effectively reduce the random errors in conditioning factors to decrease the LSP uncertainties.(2)With the proportions of random errors increasing from 5%to 20%,the LSP uncertainty increases continuously.(3)The original factors-based models are feasible for LSP in the absence of more accurate conditioning factors.(4)The influence degrees of two uncertainty issues,machine learning models and different proportions of random errors,on the LSP modeling are large and basically the same.(5)The Shapley values effectively explain the internal mechanism of machine learning model predicting landslide sus-ceptibility.In conclusion,greater proportion of random errors in conditioning factors results in higher LSP uncertainty,and low-pass filter can effectively reduce these random errors.
基金supported by the National Key R&D Program of China(2017YFF0205600)the International Research Cooperation Seed Fund of Beijing University of Technology(2018A08)+1 种基金Science and Technology Project of Beijing Municipal Commission of Transport(2018-kjc-01-213)the Construction of Service Capability of Scientific and Technological Innovation-Municipal Level of Fundamental Research Funds(Scientific Research Categories)of Beijing City(PXM2019_014204_500032).
文摘In modern transportation,pavement is one of the most important civil infrastructures for the movement of vehicles and pedestrians.Pavement service quality and service life are of great importance for civil engineers as they directly affect the regular service for the users.Therefore,monitoring the health status of pavement before irreversible damage occurs is essential for timely maintenance,which in turn ensures public transportation safety.Many pavement damages can be detected and analyzed by monitoring the structure dynamic responses and evaluating road surface conditions.Advanced technologies can be employed for the collection and analysis of such data,including various intrusive sensing techniques,image processing techniques,and machine learning methods.This review summarizes the state-ofthe-art of these three technologies in pavement engineering in recent years and suggests possible developments for future pavement monitoring and analysis based on these approaches.
基金supported by the National Natural Science Foundation of China (Nos 40974066 and 40821062)National Basic Research Program of China (No 2007CB209602)
文摘General purpose graphic processing unit （GPU） calculation technology is gradually widely used in various fields. Its mode of single instruction, multiple threads is capable of seismic numerical simulation which has a huge quantity of data and calculation steps. In this study, we introduce a GPU-based parallel calculation method of a precise integration method （PIM） for seismic forward modeling. Compared with CPU single-core calculation, GPU parallel calculating perfectly keeps the features of PIM, which has small bandwidth, high accuracy and capability of modeling complex substructures, and GPU calculation brings high computational efficiency, which means that high-performing GPU parallel calculation can make seismic forward modeling closer to real seismic records.
基金partially funded through a graduate student grant received from Northeast Sustainable Agriculture Research and Education(GNE14-078)
文摘Faba bean(Vicia faba L.)has been identified as a rich source of L-DOPA,which is used in treating Parkinson's disease.Biosynthesis and accumulation of active substances such as L-DOPA in plant tissues may interact with growing conditions and processing methods.Accumulation trends of L-DOPA in various faba bean organs and the effect of drought stress and N fertilization on L-DOPA content were studied in a field and two greenhouse experiments.The influence of various processing methods on L-DOPA content of faba bean tissues was evaluated.The highest L-DOPA content was detected in fresh leaves(22.4 mg g^(-1))followed by flowers,young pods,mature seeds,and roots.Regardless of processing method,L-DOPA concentration in faba bean tissues was significantly reduced when tissues were boiled or dried.Among various methods of processing,freezing had the lowest detrimental effect,reducing L-DOPA concentrations by 24.1%and 21.1%in leaves and seeds,respectively.Drought stress elevated L-DOPA concentration,and maximum L-DOPA(23.3 mg g^(-1)of biomass)was extracted from plants grown under severe drought stress.However,L-DOPA yield(L-DOPA concentration×biomass)was compromised,owing to the adverse influence of drought stress on dry matter production.No significant difference in L-DOPA concentration was detected among various N application rates.
