Volumetric lattice Boltzmann method for pore-scale mass diffusionadvection process in geopolymer porous structures

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.

Cascading multi-segment rupture process of the 2023 Turkish earthquake doublet on a complex fault system revealed by teleseismic P wave back projection method

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.

Correlations between mineral composition and mechanical properties of granite using digital image processing and discrete element method

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.

Machine Learning-based Identification of Contaminated Images in Light Curve Data Preprocessing

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.

Impact of three different processing methods on the digestibility and allergenicity of Chinese mitten crab(Eriocheir sinensis)tropomyosin

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.

Application and evaluation of layering shear method in LADCP data processing

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.

A Distributed Newton Method for Processing Signals Defined on the Large-Scale Networks

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.

A New Method of Frequency Fluctuation Estimation and IPS Processing Results Based on the Downlink Signal 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.

Impact of Selected Processing Methods of High-Level Cyanide in Cassava on Optic Neuropathy in Wistar Albino Rats—An Experimental Study

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-/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 9th 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.

Influence of Different Processing Methods on Honeysuckle Quality

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.

Analysis of morphological characteristics of gravels based on digital image processing technology and self-organizing map

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.

The State-of-the-Art Review on Applications of Intrusive Sensing,Image Processing Techniques,and Machine Learning Methods in Pavement Monitoring and Analysis

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.

Optimization of a precise integration method for seismic modeling based on graphic processing unit

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.

Accumulation of L-DOPA in various organs of faba bean and influence of drought, nitrogen stress, and processing methods on L-DOPA yield

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.

Effects of different processing methods on the lipid composition of hazelnut oil:a lipidomics analysis

Although hazelnut oil is rich in nutrients,its quality is greatly affected by how it is processed.However,no studies to date have comprehensively analyzed the lipid composition of hazelnut oil using different processing methods.Here,we conducted a lipidomics analysis using UPLC-QTOF-MS to characterize the lipid composition of cold-pressed hazelnut oil(CPO),ultrasonic-assisted hexane hazelnut oil(UHO)and enzyme-assisted aqueous hazelnut oil(EAO).A total of 10 subclasses of 98 lipids were identified,including35 glycerolipids(GLs),56 glycerophospholipids(GPs)and 7 sphingolipids(SPs).The total lipid and GL content were the highest in CPO,GP content was the highest in UHO and the ceramide content in SPs was most abundant in EAO.Multivariate statistical analysis showed that the lipid profiles of hazelnut oil prepared with different processing methods varied.Twelve significantly different lipids(TAG 54:3,TAG 52:2,TAG54:4,TAG 54:2,TAG 52:3,TAG 54:5,DAG 36:2,DAG 36:4,DAG 36:3,PC 36:2,PA 36:2 and PE 36:3)were identified,and these lipids could potentially be used as biomarkers to distinguish between hazelnut oil subjected to different processing methods.Our results provide useful information for hazelnut oil applications and new insight into the effects of edible oil processing.

Improvement Detecting Method of Optical Axes Parallelism of Shipboard Photoelectrical Theodolite Based on Image Processing

An improvement detecting method was proposed according to the disadvantages of testing method of optical axes parallelism of shipboard photoelectrical theodolite (short for theodolite) based on image processing. Pointolite replaced 0.2'' collimator to reduce the errors of crosshair images processing and improve the quality of image. What’s more, the high quality images could help to optimize the image processing method and the testing accuracy. The errors between the trial results interpreted by software and the results tested in dock were less than 10'', which indicated the improve method had some actual application values.

A new method of characterizing equivalent strain for equal channel angular processing

In order to establish the quantitative relationship between equivalent strain and the performance index of the deformed material within the range of certain passes for equal channel angular processing （ECAP）, a new approach to characterize the equivalent strain was proposed. The results show that there exists better accordance between mechanical property （such as hardness or strength） and equivalent strain after rolling and ECAP in a certain range of deformation amount, and Gauss equation can be satisfied among the equivalent strain and the mechanical properties for ECAP. Through regression analysis on the data of hardness and strength after the deformation, a more generalized expression of equivalent strain for ECAP is proposed as：ε=k0exp[-（k1M-k2）^2], where M is the strength or hardness of the material, k1 is the modified coefficient （k1∈ （0, 1））, ko and k2 are two parameters dependent on the critical strain and mechanical property that reaches saturation state for the material, respectively. In this expression the equivalent strain for ECAP is characterized novelly through the mechanical parameter relating to material property rather than the classical geometry equation.

Alunite processing method selection using the AHP and TOPSIS approaches under fuzzy environment

Alunite is the most important non bauxite resource for alumina. Various methods have been proposed and patented for processing alunite, but none has been performed at industrial scale and no technical,operational and economic data is available to evaluate methods. In addition, selecting the right approach for alunite beneficiation, requires introducing a wide range of criteria and careful analysis of alternatives.In this research, after studying the existing processes, 13 methods were considered and evaluated by 14 technical, economic and environmental analyzing criteria. Due to multiplicity of processing methods and attributes, in this paper, Multi Attribute Decision Making methods were employed to examine the appropriateness of choices. The Delphi Analytical Hierarchy Process(DAHP) was used for weighting selection criteria and Fuzzy TOPSIS approach was used to determine the most profitable candidates. Among 13 studied methods, Spanish, Svoronos and Hazan methods were respectively recognized to be the best choices.

Improvements of Traditional Laser Fraunhofer Diffraction Experiment Using Digital Image Processing Method

We present an improved digital image processing(DIP)method to calculate the widths of single slits.Different from the traditional laser Fraunhofer diffraction experiment in college physical experiments,by performing fast Fourier transform,inverse fast Fourier transform and the nonlinear leastsquare fitting on the diffraction pattern taken by a camera,the DIP method can quickly return an analytic expression,whose period is used to calculate widths of single slits.By comparing the measured results by the DIP method and the successional difference(SD)method,we find that for a single slit whose width is 60372μm,the DIP method is more accurate.Experimental results show that for single slits with widths between 40μm and 160μm,the relative error of the DIP method is less than 2.78%.Also,the DIP method can be used to measure the diameter of filament and fibres online in real time.

A new PAT application: Optimization of processing methods for honeysuckle flower (Lonicerae Japonicae Flos) and wild honeysuckle flower (Lonicerae Flos)

Objective:A novel processing analytical framework of Chinese Material Medica (CMM) includes breeding process analysis,planting process analysis,producing process analysis and manufacture process analysis.In order to study this framework,we used quality control of honeysuckle flower (Lonicerae japonicae Flos) including diploid and tetraploid Lonicera japonica,and wild honeysuckle flower (Lonicerae Flos) including Lonicerae hypoglauca,Lonicerae confusa,Lonicerae fulvotomentosa and Lonicerae macranthoides as an example.Methods:A total of 360 samples were analyzed from three variables including species,growing areas,and optimization of processing methods.For quantitative analysis,chlorogenic acid (CA),isochlorogenic acid A (3,5-DCA),and isochlorogenic acid C (4,5-DCA) were measured with high performance liquid chromatography (HPLC).Results:The three organic acids contents are higher in wild honeysuckle flower than honeysuckle flower;L.japonica (tetraploid) is higher than L.japonica (diploid).Modern processing methods (kill-enzyme torrefaction and fixing machine drying) are popular in growing areas and are superior to traditional methods (sun and shade drying).Conclusions:Novel process analysis concepts in processing analytical technology (PAT) enriched the Chinese MateHal Medica contents.