[Objectives]To compare the effects of traditional processing and fresh processing on the quality of Polygonatum odoratum decoction piece.[Methods]The effects of fresh processing and traditional processing on the quali...[Objectives]To compare the effects of traditional processing and fresh processing on the quality of Polygonatum odoratum decoction piece.[Methods]The effects of fresh processing and traditional processing on the quality of P.odoratum decoction piece were compared and analyzed with appearance characteristics,total ash content,extract content,total polysaccharides content,and total flavonoids content as the evaluation indexes.[Results]Fresh processing method in different production areas has different effects on P.odoratum decoction piece.P.odoratum was dried in oven of 50℃.When moisture content was 41.44%-59.67%,it was cut.After complete drying at 50℃,the moisture content of dried P.odoratum was 8.94%-9.60%,and ethanol-soluble extract content was 77.29%-78.20%,and water-soluble extract was 77.7%-78.14%.At this time,the appearance characteristics of section of P.odoratum decoction piece were better than that of traditional processing,which was yellowish white.The total polysaccharide content was higher than that of traditional processing,and the content of total flavonoids was statistically significant different from that of traditional processing.[Conclusions]The quality of P.odoratum decoction piece by fresh processing is better than that of the traditional processing,and it is feasible to use fresh processing.展开更多
In recent years, the widespread adoption of parallel computing, especially in multi-core processors and high-performance computing environments, ushered in a new era of efficiency and speed. This trend was particularl...In recent years, the widespread adoption of parallel computing, especially in multi-core processors and high-performance computing environments, ushered in a new era of efficiency and speed. This trend was particularly noteworthy in the field of image processing, which witnessed significant advancements. This parallel computing project explored the field of parallel image processing, with a focus on the grayscale conversion of colorful images. Our approach involved integrating OpenMP into our framework for parallelization to execute a critical image processing task: grayscale conversion. By using OpenMP, we strategically enhanced the overall performance of the conversion process by distributing the workload across multiple threads. The primary objectives of our project revolved around optimizing computation time and improving overall efficiency, particularly in the task of grayscale conversion of colorful images. Utilizing OpenMP for concurrent processing across multiple cores significantly reduced execution times through the effective distribution of tasks among these cores. The speedup values for various image sizes highlighted the efficacy of parallel processing, especially for large images. However, a detailed examination revealed a potential decline in parallelization efficiency with an increasing number of cores. This underscored the importance of a carefully optimized parallelization strategy, considering factors like load balancing and minimizing communication overhead. Despite challenges, the overall scalability and efficiency achieved with parallel image processing underscored OpenMP’s effectiveness in accelerating image manipulation tasks.展开更多
In order to obtain Mg alloys with fine microstructures and high mechanical performances,a novel friction-based processing method,name as“constrained friction processing(CFP)”,was investigated.Via CFP,defect-free Mg-...In order to obtain Mg alloys with fine microstructures and high mechanical performances,a novel friction-based processing method,name as“constrained friction processing(CFP)”,was investigated.Via CFP,defect-free Mg-Zn-Ca rods with greatly refined grains and high mechanical properties were produced.Compared to the previous as-cast microstructure,the grain size was reduced from more than 1 mm to around 4μm within 3 s by a single process cycle.The compressive yield strength was increased by 350%while the ultimate compressive strength by 53%.According to the established material flow behaviors by“tracer material”,the plastic material was transported by shear deformation.From the base material to the rod,the material experienced three stages,i.e.deformation by the tool,upward flow with additional tilt,followed by upward transportation.The microstructural evolution was revealed by“stop-action”technique.The microstructural development at regions adjacent to the rod is mainly controlled by twinning,dynamic recrystallization(DRX)as well as particle stimulated nucleation,while that within the rod is related to DRX combined with grain growth.展开更多
Nowadays,magnesium alloys are emerging in biomedical implants for their similar properties to natural bones.However,the rapid degradation of magnesium alloys in biological media hinders successful implantation.Refinem...Nowadays,magnesium alloys are emerging in biomedical implants for their similar properties to natural bones.However,the rapid degradation of magnesium alloys in biological media hinders successful implantation.Refinement of microstructure,as well as reinforcement particles can significantly improve the degradation rate.In this work,multi-pass friction stir processing(FSP)was proposed to synthesize WE43/nano-hydroxyapatite(n HA)surface composite,the microstructure,reinforced particle distribution,micro-hardness,corrosion behavior and in-vitro bioactivity were studied.The subsequent FSP passes of WE43 alloy and WE43/n HA composite refined the grain size which was reduced by 94.29%and 95.92%(2.63 and 1.88μm,respectively)compared to base metal after three passes.This resulted in increasing the microhardness by 120%(90.86 HV0.1)and 135%(105.59 HV0.1)for the WE43 and WE43-n HA,respectively.It is found that increasing FSP passes improved the uniform distribution of n HA particles within the composite matrix which led to improved corrosion resistance and less degradation rate.The corrosion rate of the FSPed WE43/n HA composite after three passes was reduced by 38.2%(4.13 mm/year)and the degradation rate was reduced by 69.7%(2.87 mm/y).This is attributed to secondary phase(Mg24Y5and Mg41Nd5)particle fragmentation and redistribution,as well as a homogeneous distribution of n HA.Additionally,the growing Ca-P and Mg(OH)2layer formed on the surface represented a protective layer that reduced the degradation rate.The wettability test revealed a relatively hydrophilic surface with water contact angle of 49.1±2.2°compared to 71.2±2.1°for base metal.Also,biomineralization test showed that apatite layer grew after immersion 7d in simulated body fluid with atomic ratio of Ca/P 1.60 approaching the stoichiometric ratio(1.67)indicating superior bioactivity of FSPed WE43/n HA composite after three passes.These results raise that the grain refinement by FSP and introduction of n HA particles significantly improved the degradation rate and in-vitro bioactivity of WE43 alloy for biomedical applications.展开更多
The sensory perception of food is a dynamic process,which is closely related to the release of flavor substances during oral processing.It’s not only affected by the food material,but also subjected to the individual...The sensory perception of food is a dynamic process,which is closely related to the release of flavor substances during oral processing.It’s not only affected by the food material,but also subjected to the individual oral environment.To explore the oral processing characteristics of soft-boiled chicken,the sensory properties,texture,particle size,viscosity,characteristic values of electronic nose and tongue of different chicken samples were investigated.The correlation analysis showed that the physical characteristics especially the cohesiveness,springiness,resilience of the sample determined oral processing behavior.The addition of chicken skin played a role in lubrication during oral processing.The particle size of the bolus was heightened at the early stage,and the fluidity was enhanced in the end,which reduced the chewing time to the swallowing point and raised the aromatic compounds signal of electronic nose.But the effect of chicken skin on chicken thigh with relatively high fat content,was opposite in electronic nose,which had a certain masking effect on the perception of umami and sweet taste.In conclusion,fat played a critical role in chicken oral processing and chicken thigh had obvious advantages in comprehensive evaluation of soft-boiled chicken,which was more popular among people.展开更多
Food allergens are mainly naturally-occurring proteins with immunoglobulin E(IgE)-binding epitopes.Understanding the structural and immunogenic characteristics of allergenic proteins is essential in assessing whether ...Food allergens are mainly naturally-occurring proteins with immunoglobulin E(IgE)-binding epitopes.Understanding the structural and immunogenic characteristics of allergenic proteins is essential in assessing whether and how food processing techniques reduce allergenicity.We here discuss the impacts of food processing technologies on the modification of physicochemical,structural,and immunogenic properties of allergenic proteins.Detection techniques for characterizing changes in these properties of food allergens are summarized.Food processing helps to reduce allergenicity by aggregating or denaturing proteins,which masks,modifies,or destroys antigenic epitopes,whereas,it cannot eliminate allergenicity completely,and sometimes even improves allergenicity by exposing new epitopes.Moreover,most food processing techniques have been tested on purified food allergens rather than food products due to potential interference of other food components.We provide guidance for further development of processing operations that can decrease the allergenicity of allergenic food proteins without negatively impacting the nutritional profile.展开更多
In the process of production or processing of materials by various methods,there is a need for a large volume of water of the required quality.Today in many regions of the world,there is an acute problem of providing ...In the process of production or processing of materials by various methods,there is a need for a large volume of water of the required quality.Today in many regions of the world,there is an acute problem of providing industry with water of a required quality.Its solution is an urgent and difficult task.The water quality of surface water bodies is formed by a combination of a large number of both natural and anthropogenic factors,and is often significantly heterogeneous not only in the water area,but also in depth.As a rule,the water supply of large industrial enterprises is located along the river network.Mergers are the most important nodes of river systems.Understanding the mechanism of transport of pollutants at the confluence of rivers is critical for assessing water quality.In recent years,thanks to the data of satellite images,the interest of researchers in the phenomenon of mixing the waters of merging rivers has increased.The nature of the merger is influenced by the formation of transverse circulation.Within the framework of this work,a study of vorticity,as well as the width of the mixing zone,depending on the distance from the confluence,the speeds of the merging rivers and the angle of confluence was carried out.Since the consumer properties of water are largely determined by its chemical and physical indicators,the intensity of mixing,determined largely by the nature of the secondary circulation,is of fundamental importance for assessing the distribution of hydrochemical indicators of water quality in the mixing zone.These characteristics are important not only for organizing water intake for drinking and technical purposes with the best consumer properties,but also for organizing an effective monitoring system for confluence zones.展开更多
Unstructured and irregular graph data causes strong randomness and poor locality of data accesses in graph processing.This paper optimizes the depth-branch-resorting algorithm(DBR),and proposes a branch-alternation-re...Unstructured and irregular graph data causes strong randomness and poor locality of data accesses in graph processing.This paper optimizes the depth-branch-resorting algorithm(DBR),and proposes a branch-alternation-resorting algorithm(BAR).In order to make the algorithm run in parallel and improve the efficiency of algorithm operation,the BAR algorithm is mapped onto the reconfigurable array processor(APR-16)to achieve vertex reordering,effectively improving the locality of graph data.This paper validates the BAR algorithm on the GraphBIG framework,by utilizing the reordered dataset with BAR on breadth-first search(BFS),single source shortest paht(SSSP)and betweenness centrality(BC)algorithms for traversal.The results show that compared with DBR and Corder algorithms,BAR can reduce execution time by up to 33.00%,and 51.00%seperatively.In terms of data movement,the BAR algorithm has a maximum reduction of 39.00%compared with the DBR algorithm and 29.66%compared with Corder algorithm.In terms of computational complexity,the BAR algorithm has a maximum reduction of 32.56%compared with DBR algorithm and53.05%compared with Corder algorithm.展开更多
Real-time capabilities and computational efficiency are provided by parallel image processing utilizing OpenMP. However, race conditions can affect the accuracy and reliability of the outcomes. This paper highlights t...Real-time capabilities and computational efficiency are provided by parallel image processing utilizing OpenMP. However, race conditions can affect the accuracy and reliability of the outcomes. This paper highlights the importance of addressing race conditions in parallel image processing, specifically focusing on color inverse filtering using OpenMP. We considered three solutions to solve race conditions, each with distinct characteristics: #pragma omp atomic: Protects individual memory operations for fine-grained control. #pragma omp critical: Protects entire code blocks for exclusive access. #pragma omp parallel sections reduction: Employs a reduction clause for safe aggregation of values across threads. Our findings show that the produced images were unaffected by race condition. However, it becomes evident that solving the race conditions in the code makes it significantly faster, especially when it is executed on multiple cores.展开更多
This monograph presents an overview of friction stir processing(FSP)of surface metal-matrix composites(MMCs)using the AZ91 magnesium alloy.The reported results in relation to various reinforcing particles,including si...This monograph presents an overview of friction stir processing(FSP)of surface metal-matrix composites(MMCs)using the AZ91 magnesium alloy.The reported results in relation to various reinforcing particles,including silicon carbide(SiC),alumina(Al_(2)O_(3)),quartz(SiO_(2)),boron carbide(B_(4)C),titanium carbide(TiC),carbon fiber,hydroxyapatite(HA),in-situ formed phases,and hybrid reinforcements are summarized.AZ91 composite fabricating methods based on FSP are explained,including groove filling(grooving),drilled hole filling,sandwich method,stir casting followed by FSP,and formation of in-situ particles.The effects of introducing second-phase particles and FSP process parameters(e.g.,tool rotation rate,traverse speed,and the number of passes)on the microstructural modification,grain refinement,homogeneity in the distribution of particles,inhibition of grain growth,mechanical properties,strength–ductility trade-off,wear/tribological behavior,and corrosion resistance are discussed.Finally,useful suggestions for future work are proposed,including focusing on the superplasticity and superplastic forming,metal additive manufacturing processes based on friction stir engineering(such as additive friction stir deposition),direct FSP,stationary shoulder FSP,correlation of the dynamic recrystallization(DRX)grain size with the Zener–Hollomon parameter similar to hot deformation studies,process parameters(such as the particle volume fraction and external cooling),and common reinforcing phases such as zirconia(ZrO_(2))and carbon nanotubes(CNTs).展开更多
The networks are fundamental to our modern world and they appear throughout science and society.Access to a massive amount of data presents a unique opportunity to the researcher’s community.As networks grow in size ...The networks are fundamental to our modern world and they appear throughout science and society.Access to a massive amount of data presents a unique opportunity to the researcher’s community.As networks grow in size the complexity increases and our ability to analyze them using the current state of the art is at severe risk of failing to keep pace.Therefore,this paper initiates a discussion on graph signal processing for large-scale data analysis.We first provide a comprehensive overview of core ideas in Graph signal processing(GSP)and their connection to conventional digital signal processing(DSP).We then summarize recent developments in developing basic GSP tools,including methods for graph filtering or graph learning,graph signal,graph Fourier transform(GFT),spectrum,graph frequency,etc.Graph filtering is a basic task that allows for isolating the contribution of individual frequencies and therefore enables the removal of noise.We then consider a graph filter as a model that helps to extend the application of GSP methods to large datasets.To show the suitability and the effeteness,we first created a noisy graph signal and then applied it to the filter.After several rounds of simulation results.We see that the filtered signal appears to be smoother and is closer to the original noise-free distance-based signal.By using this example application,we thoroughly demonstrated that graph filtration is efficient for big data analytics.展开更多
Withthe rapiddevelopment of deep learning,the size of data sets anddeepneuralnetworks(DNNs)models are also booming.As a result,the intolerable long time for models’training or inference with conventional strategies c...Withthe rapiddevelopment of deep learning,the size of data sets anddeepneuralnetworks(DNNs)models are also booming.As a result,the intolerable long time for models’training or inference with conventional strategies can not meet the satisfaction of modern tasks gradually.Moreover,devices stay idle in the scenario of edge computing(EC),which presents a waste of resources since they can share the pressure of the busy devices but they do not.To address the problem,the strategy leveraging distributed processing has been applied to load computation tasks from a single processor to a group of devices,which results in the acceleration of training or inference of DNN models and promotes the high utilization of devices in edge computing.Compared with existing papers,this paper presents an enlightening and novel review of applying distributed processing with data and model parallelism to improve deep learning tasks in edge computing.Considering the practicalities,commonly used lightweight models in a distributed system are introduced as well.As the key technique,the parallel strategy will be described in detail.Then some typical applications of distributed processing will be analyzed.Finally,the challenges of distributed processing with edge computing will be described.展开更多
With the continued development of multiple Global Navigation Satellite Systems(GNSS)and the emergence of various frequencies,UnDifferenced and UnCombined(UDUC)data processing has become an increasingly attractive opti...With the continued development of multiple Global Navigation Satellite Systems(GNSS)and the emergence of various frequencies,UnDifferenced and UnCombined(UDUC)data processing has become an increasingly attractive option.In this contribution,we provide an overview of the current status of UDUC GNSS data processing activities in China.These activities encompass the formulation of Precise Point Positioning(PPP)models and PPP-Real-Time Kinematic(PPP-RTK)models for processing single-station and multi-station GNSS data,respectively.Regarding single-station data processing,we discuss the advancements in PPP models,particularly the extension from a single system to multiple systems,and from dual frequencies to single and multiple frequencies.Additionally,we introduce the modified PPP model,which accounts for the time variation of receiver code biases,a departure from the conventional PPP model that typically assumes these biases to be time-constant.In the realm of multi-station PPP-RTK data processing,we introduce the ionosphere-weighted PPP-RTK model,which enhances the model strength by considering the spatial correlation of ionospheric delays.We also review the phase-only PPP-RTK model,designed to mitigate the impact of unmodelled code-related errors.Furthermore,we explore GLONASS PPP-RTK,achieved through the application of the integer-estimable model.For large-scale network data processing,we introduce the all-in-view PPP-RTK model,which alleviates the strict common-view requirement at all receivers.Moreover,we present the decentralized PPP-RTK data processing strategy,designed to improve computational efficiency.Overall,this work highlights the various advancements in UDUC GNSS data processing,providing insights into the state-of-the-art techniques employed in China to achieve precise GNSS applications.展开更多
Deep learning(DL) is progressively popular as a viable alternative to traditional signal processing(SP) based methods for fault diagnosis. However, the lack of explainability makes DL-based fault diagnosis methods dif...Deep learning(DL) is progressively popular as a viable alternative to traditional signal processing(SP) based methods for fault diagnosis. However, the lack of explainability makes DL-based fault diagnosis methods difficult to be trusted and understood by industrial users. In addition, the extraction of weak fault features from signals with heavy noise is imperative in industrial applications. To address these limitations, inspired by the Filterbank-Feature-Decision methodology, we propose a new Signal Processing Informed Neural Network(SPINN) framework by embedding SP knowledge into the DL model. As one of the practical implementations for SPINN, a denoising fault-aware wavelet network(DFAWNet) is developed, which consists of fused wavelet convolution(FWConv), dynamic hard thresholding(DHT),index-based soft filtering(ISF), and a classifier. Taking advantage of wavelet transform, FWConv extracts multiscale features while learning wavelet scales and selecting important wavelet bases automatically;DHT dynamically eliminates noise-related components via point-wise hard thresholding;inspired by index-based filtering, ISF optimizes and selects optimal filters for diagnostic feature extraction. It’s worth noting that SPINN may be readily applied to different deep learning networks by simply adding filterbank and feature modules in front. Experiments results demonstrate a significant diagnostic performance improvement over other explainable or denoising deep learning networks. The corresponding code is available at https://github. com/alber tszg/DFAWn et.展开更多
Heavy metal ions in shellfish products are harmful to human health,and their removal with low nutrient loss remains challenging.Herein,a new type of mesoporous silica(SBA15),modified internally with ammonium pyrrolidi...Heavy metal ions in shellfish products are harmful to human health,and their removal with low nutrient loss remains challenging.Herein,a new type of mesoporous silica(SBA15),modified internally with ammonium pyrrolidine dithiocarbamate(APDC)and externally with alkyl-diol groups,which was named as Diol-APDC-SBA15,was successfully developed and characterized by powder X-ray diffraction patterns,nitrogen adsorption,and Fourier transform infrared spectroscopy.The solutions with lead,chromium,cadmium,and copper were used to investigate the adsorption capacity of Diol-APDC-SBA15.Diol-APDC-SBA15 was adopted to remove heavy metals from cooking liquids of clams(Ruditapes philippinarum),hydrolysate liquids of oysters(Ostrea gigas Thunberg),and polysaccharide solution from the cooking liquid of R.philippinarum.The efficiencies of removing heavy metal ions and the loss rates of proteins and polysaccharides were examined.The results showed that the adsorption capacities of Diol-APDCSBA15 for Pb,Cr,Cd,and Cu in standard heavy-metal solutions were 161.4,166.1,29.6,and 60.2mgg^(−1),respectively.The removal efficiency of Diol-APDC-SBA15 for Pb in the three shellfish processing liquids ranged from 60.5%to 99.6%.The Cr removal efficiency was above 99.9%in the oyster hydrolysate liquid.Meanwhile,the percentages of polysaccharide loss were 5.5%and 3.7%in the cooking liquid of clam and polysaccharide solution,respectively,and the protein loss was 1.2%in the oyster hydrolysate liquid.Therefore,the Diol-APDC-SBA15 material exhibits a great potential application in the removal of heavy metals from shellfish processing liquids with low losses of proteins and polysaccharides.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
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
Large structures,such as bridges,highways,etc.,need to be inspected to evaluate their actual physical and functional condition,to predict future conditions,and to help decision makers allocating maintenance and rehabi...Large structures,such as bridges,highways,etc.,need to be inspected to evaluate their actual physical and functional condition,to predict future conditions,and to help decision makers allocating maintenance and rehabilitation resources.The assessment of civil infrastructure condition is carried out through information obtained by inspection and/or monitoring operations.Traditional techniques in structural health monitoring(SHM)involve visual inspection related to inspection standards that can be time-consuming data collection,expensive,labor intensive,and dangerous.To address these limitations,machine vision-based inspection procedures have increasingly been investigated within the research community.In this context,this paper proposes and compares four different computer vision procedures to identify damage by image processing:Otsu method thresholding,Markov random fields segmentation,RGB color detection technique,and K-means clustering algorithm.The first method is based on segmentation by thresholding that returns a binary image from a grayscale image.The Markov random fields technique uses a probabilistic approach to assign labels to model the spatial dependencies in image pixels.The RGB technique uses color detection to evaluate the defect extensions.Finally,K-means algorithm is based on Euclidean distance for clustering of the images.The benefits and limitations of each technique are discussed,and the challenges of using the techniques are highlighted.To show the effectiveness of the described techniques in damage detection of civil infrastructures,a case study is presented.Results show that various types of corrosion and cracks can be detected by image processing techniques making the proposed techniques a suitable tool for the prediction of the damage evolution in civil infrastructures.展开更多
基金Supported by Guangxi Science and Technology Major Project(GUIKE AA22096020)Central Guidance for Local Scientific and Technological Development Funds(ZY20230102)+2 种基金Guilin City Science Research and Technology Development Plan Project(20220104-4,20210202-1,2020011203-1,2020011203-2)Open Project of Guangxi Key Laboratory of Tumor Immunology and Microenvironment Regulation(2022KF005)College Students Innovative Entrepreneurial Training Plan Program(202210601015).
文摘[Objectives]To compare the effects of traditional processing and fresh processing on the quality of Polygonatum odoratum decoction piece.[Methods]The effects of fresh processing and traditional processing on the quality of P.odoratum decoction piece were compared and analyzed with appearance characteristics,total ash content,extract content,total polysaccharides content,and total flavonoids content as the evaluation indexes.[Results]Fresh processing method in different production areas has different effects on P.odoratum decoction piece.P.odoratum was dried in oven of 50℃.When moisture content was 41.44%-59.67%,it was cut.After complete drying at 50℃,the moisture content of dried P.odoratum was 8.94%-9.60%,and ethanol-soluble extract content was 77.29%-78.20%,and water-soluble extract was 77.7%-78.14%.At this time,the appearance characteristics of section of P.odoratum decoction piece were better than that of traditional processing,which was yellowish white.The total polysaccharide content was higher than that of traditional processing,and the content of total flavonoids was statistically significant different from that of traditional processing.[Conclusions]The quality of P.odoratum decoction piece by fresh processing is better than that of the traditional processing,and it is feasible to use fresh processing.
文摘In recent years, the widespread adoption of parallel computing, especially in multi-core processors and high-performance computing environments, ushered in a new era of efficiency and speed. This trend was particularly noteworthy in the field of image processing, which witnessed significant advancements. This parallel computing project explored the field of parallel image processing, with a focus on the grayscale conversion of colorful images. Our approach involved integrating OpenMP into our framework for parallelization to execute a critical image processing task: grayscale conversion. By using OpenMP, we strategically enhanced the overall performance of the conversion process by distributing the workload across multiple threads. The primary objectives of our project revolved around optimizing computation time and improving overall efficiency, particularly in the task of grayscale conversion of colorful images. Utilizing OpenMP for concurrent processing across multiple cores significantly reduced execution times through the effective distribution of tasks among these cores. The speedup values for various image sizes highlighted the efficacy of parallel processing, especially for large images. However, a detailed examination revealed a potential decline in parallelization efficiency with an increasing number of cores. This underscored the importance of a carefully optimized parallelization strategy, considering factors like load balancing and minimizing communication overhead. Despite challenges, the overall scalability and efficiency achieved with parallel image processing underscored OpenMP’s effectiveness in accelerating image manipulation tasks.
基金the China Scholarship Council for the award of fellowship and funding(No.202006230137)。
文摘In order to obtain Mg alloys with fine microstructures and high mechanical performances,a novel friction-based processing method,name as“constrained friction processing(CFP)”,was investigated.Via CFP,defect-free Mg-Zn-Ca rods with greatly refined grains and high mechanical properties were produced.Compared to the previous as-cast microstructure,the grain size was reduced from more than 1 mm to around 4μm within 3 s by a single process cycle.The compressive yield strength was increased by 350%while the ultimate compressive strength by 53%.According to the established material flow behaviors by“tracer material”,the plastic material was transported by shear deformation.From the base material to the rod,the material experienced three stages,i.e.deformation by the tool,upward flow with additional tilt,followed by upward transportation.The microstructural evolution was revealed by“stop-action”technique.The microstructural development at regions adjacent to the rod is mainly controlled by twinning,dynamic recrystallization(DRX)as well as particle stimulated nucleation,while that within the rod is related to DRX combined with grain growth.
基金supported by the University Malaya(Grant code:FRGS/1/2022/TK10/UM/02/6)the National Natural Science Foundation of China(Grant No.51275414,No.51605387)Deanship of Scientific Research at King Khalid University for funding this work through the Large Groups Project under grant number RGP.2/303/44。
文摘Nowadays,magnesium alloys are emerging in biomedical implants for their similar properties to natural bones.However,the rapid degradation of magnesium alloys in biological media hinders successful implantation.Refinement of microstructure,as well as reinforcement particles can significantly improve the degradation rate.In this work,multi-pass friction stir processing(FSP)was proposed to synthesize WE43/nano-hydroxyapatite(n HA)surface composite,the microstructure,reinforced particle distribution,micro-hardness,corrosion behavior and in-vitro bioactivity were studied.The subsequent FSP passes of WE43 alloy and WE43/n HA composite refined the grain size which was reduced by 94.29%and 95.92%(2.63 and 1.88μm,respectively)compared to base metal after three passes.This resulted in increasing the microhardness by 120%(90.86 HV0.1)and 135%(105.59 HV0.1)for the WE43 and WE43-n HA,respectively.It is found that increasing FSP passes improved the uniform distribution of n HA particles within the composite matrix which led to improved corrosion resistance and less degradation rate.The corrosion rate of the FSPed WE43/n HA composite after three passes was reduced by 38.2%(4.13 mm/year)and the degradation rate was reduced by 69.7%(2.87 mm/y).This is attributed to secondary phase(Mg24Y5and Mg41Nd5)particle fragmentation and redistribution,as well as a homogeneous distribution of n HA.Additionally,the growing Ca-P and Mg(OH)2layer formed on the surface represented a protective layer that reduced the degradation rate.The wettability test revealed a relatively hydrophilic surface with water contact angle of 49.1±2.2°compared to 71.2±2.1°for base metal.Also,biomineralization test showed that apatite layer grew after immersion 7d in simulated body fluid with atomic ratio of Ca/P 1.60 approaching the stoichiometric ratio(1.67)indicating superior bioactivity of FSPed WE43/n HA composite after three passes.These results raise that the grain refinement by FSP and introduction of n HA particles significantly improved the degradation rate and in-vitro bioactivity of WE43 alloy for biomedical applications.
基金supported by China Agriculture Research System of MOF and MARA(CARS-41)Wens Fifth Five R&D Major Project(WENS-2020-1-ZDZX-007)。
文摘The sensory perception of food is a dynamic process,which is closely related to the release of flavor substances during oral processing.It’s not only affected by the food material,but also subjected to the individual oral environment.To explore the oral processing characteristics of soft-boiled chicken,the sensory properties,texture,particle size,viscosity,characteristic values of electronic nose and tongue of different chicken samples were investigated.The correlation analysis showed that the physical characteristics especially the cohesiveness,springiness,resilience of the sample determined oral processing behavior.The addition of chicken skin played a role in lubrication during oral processing.The particle size of the bolus was heightened at the early stage,and the fluidity was enhanced in the end,which reduced the chewing time to the swallowing point and raised the aromatic compounds signal of electronic nose.But the effect of chicken skin on chicken thigh with relatively high fat content,was opposite in electronic nose,which had a certain masking effect on the perception of umami and sweet taste.In conclusion,fat played a critical role in chicken oral processing and chicken thigh had obvious advantages in comprehensive evaluation of soft-boiled chicken,which was more popular among people.
基金supported by the National Natural Science Foundation of China (32102605)the Agricultural Science and Technology Innovation Program under Grant (CAAS-ASTIP-2020IAR)the Earmarked Fund for CARS (CARS-44)。
文摘Food allergens are mainly naturally-occurring proteins with immunoglobulin E(IgE)-binding epitopes.Understanding the structural and immunogenic characteristics of allergenic proteins is essential in assessing whether and how food processing techniques reduce allergenicity.We here discuss the impacts of food processing technologies on the modification of physicochemical,structural,and immunogenic properties of allergenic proteins.Detection techniques for characterizing changes in these properties of food allergens are summarized.Food processing helps to reduce allergenicity by aggregating or denaturing proteins,which masks,modifies,or destroys antigenic epitopes,whereas,it cannot eliminate allergenicity completely,and sometimes even improves allergenicity by exposing new epitopes.Moreover,most food processing techniques have been tested on purified food allergens rather than food products due to potential interference of other food components.We provide guidance for further development of processing operations that can decrease the allergenicity of allergenic food proteins without negatively impacting the nutritional profile.
基金financial support from the Government of the Perm Territory within the Framework of Scientific Project No.S-26/828the Ministry of Science and High Education of Russia(Theme No.121031700169-1).
文摘In the process of production or processing of materials by various methods,there is a need for a large volume of water of the required quality.Today in many regions of the world,there is an acute problem of providing industry with water of a required quality.Its solution is an urgent and difficult task.The water quality of surface water bodies is formed by a combination of a large number of both natural and anthropogenic factors,and is often significantly heterogeneous not only in the water area,but also in depth.As a rule,the water supply of large industrial enterprises is located along the river network.Mergers are the most important nodes of river systems.Understanding the mechanism of transport of pollutants at the confluence of rivers is critical for assessing water quality.In recent years,thanks to the data of satellite images,the interest of researchers in the phenomenon of mixing the waters of merging rivers has increased.The nature of the merger is influenced by the formation of transverse circulation.Within the framework of this work,a study of vorticity,as well as the width of the mixing zone,depending on the distance from the confluence,the speeds of the merging rivers and the angle of confluence was carried out.Since the consumer properties of water are largely determined by its chemical and physical indicators,the intensity of mixing,determined largely by the nature of the secondary circulation,is of fundamental importance for assessing the distribution of hydrochemical indicators of water quality in the mixing zone.These characteristics are important not only for organizing water intake for drinking and technical purposes with the best consumer properties,but also for organizing an effective monitoring system for confluence zones.
基金the National Key R&D Program of China(No.2022ZD0119001)the National Natural Science Foundation of China(No.61834005)+3 种基金the Shaanxi Province Key R&D Plan(No.2022GY-027)the Key Scientific Research Project of Shaanxi Department of Education(No.22JY060)the Education Research Project of XUPT(No.JGA202108)the Graduate Student Innovation Fund of Xi'an University of Posts and Telecommunications(No.CXJJZL2022011)。
文摘Unstructured and irregular graph data causes strong randomness and poor locality of data accesses in graph processing.This paper optimizes the depth-branch-resorting algorithm(DBR),and proposes a branch-alternation-resorting algorithm(BAR).In order to make the algorithm run in parallel and improve the efficiency of algorithm operation,the BAR algorithm is mapped onto the reconfigurable array processor(APR-16)to achieve vertex reordering,effectively improving the locality of graph data.This paper validates the BAR algorithm on the GraphBIG framework,by utilizing the reordered dataset with BAR on breadth-first search(BFS),single source shortest paht(SSSP)and betweenness centrality(BC)algorithms for traversal.The results show that compared with DBR and Corder algorithms,BAR can reduce execution time by up to 33.00%,and 51.00%seperatively.In terms of data movement,the BAR algorithm has a maximum reduction of 39.00%compared with the DBR algorithm and 29.66%compared with Corder algorithm.In terms of computational complexity,the BAR algorithm has a maximum reduction of 32.56%compared with DBR algorithm and53.05%compared with Corder algorithm.
文摘Real-time capabilities and computational efficiency are provided by parallel image processing utilizing OpenMP. However, race conditions can affect the accuracy and reliability of the outcomes. This paper highlights the importance of addressing race conditions in parallel image processing, specifically focusing on color inverse filtering using OpenMP. We considered three solutions to solve race conditions, each with distinct characteristics: #pragma omp atomic: Protects individual memory operations for fine-grained control. #pragma omp critical: Protects entire code blocks for exclusive access. #pragma omp parallel sections reduction: Employs a reduction clause for safe aggregation of values across threads. Our findings show that the produced images were unaffected by race condition. However, it becomes evident that solving the race conditions in the code makes it significantly faster, especially when it is executed on multiple cores.
文摘This monograph presents an overview of friction stir processing(FSP)of surface metal-matrix composites(MMCs)using the AZ91 magnesium alloy.The reported results in relation to various reinforcing particles,including silicon carbide(SiC),alumina(Al_(2)O_(3)),quartz(SiO_(2)),boron carbide(B_(4)C),titanium carbide(TiC),carbon fiber,hydroxyapatite(HA),in-situ formed phases,and hybrid reinforcements are summarized.AZ91 composite fabricating methods based on FSP are explained,including groove filling(grooving),drilled hole filling,sandwich method,stir casting followed by FSP,and formation of in-situ particles.The effects of introducing second-phase particles and FSP process parameters(e.g.,tool rotation rate,traverse speed,and the number of passes)on the microstructural modification,grain refinement,homogeneity in the distribution of particles,inhibition of grain growth,mechanical properties,strength–ductility trade-off,wear/tribological behavior,and corrosion resistance are discussed.Finally,useful suggestions for future work are proposed,including focusing on the superplasticity and superplastic forming,metal additive manufacturing processes based on friction stir engineering(such as additive friction stir deposition),direct FSP,stationary shoulder FSP,correlation of the dynamic recrystallization(DRX)grain size with the Zener–Hollomon parameter similar to hot deformation studies,process parameters(such as the particle volume fraction and external cooling),and common reinforcing phases such as zirconia(ZrO_(2))and carbon nanotubes(CNTs).
基金supported in part by Basic Science Research Program through the National Research Foundation of Korea(NRF)funded by the Ministry of Education(NRF-2019R1A2C1006159)and(NRF-2021R1A6A1A03039493)by the 2021 Yeungnam University Research Grant.
文摘The networks are fundamental to our modern world and they appear throughout science and society.Access to a massive amount of data presents a unique opportunity to the researcher’s community.As networks grow in size the complexity increases and our ability to analyze them using the current state of the art is at severe risk of failing to keep pace.Therefore,this paper initiates a discussion on graph signal processing for large-scale data analysis.We first provide a comprehensive overview of core ideas in Graph signal processing(GSP)and their connection to conventional digital signal processing(DSP).We then summarize recent developments in developing basic GSP tools,including methods for graph filtering or graph learning,graph signal,graph Fourier transform(GFT),spectrum,graph frequency,etc.Graph filtering is a basic task that allows for isolating the contribution of individual frequencies and therefore enables the removal of noise.We then consider a graph filter as a model that helps to extend the application of GSP methods to large datasets.To show the suitability and the effeteness,we first created a noisy graph signal and then applied it to the filter.After several rounds of simulation results.We see that the filtered signal appears to be smoother and is closer to the original noise-free distance-based signal.By using this example application,we thoroughly demonstrated that graph filtration is efficient for big data analytics.
基金supported by the Natural Science Foundation of Jiangsu Province of China under Grant No.BK20211284the Financial and Science Technology Plan Project of Xinjiang Production,Construction Corps under Grant No.2020DB005the National Natural Science Foundation of China under Grant Nos.61872219,62002276 and 62177014。
文摘Withthe rapiddevelopment of deep learning,the size of data sets anddeepneuralnetworks(DNNs)models are also booming.As a result,the intolerable long time for models’training or inference with conventional strategies can not meet the satisfaction of modern tasks gradually.Moreover,devices stay idle in the scenario of edge computing(EC),which presents a waste of resources since they can share the pressure of the busy devices but they do not.To address the problem,the strategy leveraging distributed processing has been applied to load computation tasks from a single processor to a group of devices,which results in the acceleration of training or inference of DNN models and promotes the high utilization of devices in edge computing.Compared with existing papers,this paper presents an enlightening and novel review of applying distributed processing with data and model parallelism to improve deep learning tasks in edge computing.Considering the practicalities,commonly used lightweight models in a distributed system are introduced as well.As the key technique,the parallel strategy will be described in detail.Then some typical applications of distributed processing will be analyzed.Finally,the challenges of distributed processing with edge computing will be described.
基金National Natural Science Foundation of China(No.42022025)。
文摘With the continued development of multiple Global Navigation Satellite Systems(GNSS)and the emergence of various frequencies,UnDifferenced and UnCombined(UDUC)data processing has become an increasingly attractive option.In this contribution,we provide an overview of the current status of UDUC GNSS data processing activities in China.These activities encompass the formulation of Precise Point Positioning(PPP)models and PPP-Real-Time Kinematic(PPP-RTK)models for processing single-station and multi-station GNSS data,respectively.Regarding single-station data processing,we discuss the advancements in PPP models,particularly the extension from a single system to multiple systems,and from dual frequencies to single and multiple frequencies.Additionally,we introduce the modified PPP model,which accounts for the time variation of receiver code biases,a departure from the conventional PPP model that typically assumes these biases to be time-constant.In the realm of multi-station PPP-RTK data processing,we introduce the ionosphere-weighted PPP-RTK model,which enhances the model strength by considering the spatial correlation of ionospheric delays.We also review the phase-only PPP-RTK model,designed to mitigate the impact of unmodelled code-related errors.Furthermore,we explore GLONASS PPP-RTK,achieved through the application of the integer-estimable model.For large-scale network data processing,we introduce the all-in-view PPP-RTK model,which alleviates the strict common-view requirement at all receivers.Moreover,we present the decentralized PPP-RTK data processing strategy,designed to improve computational efficiency.Overall,this work highlights the various advancements in UDUC GNSS data processing,providing insights into the state-of-the-art techniques employed in China to achieve precise GNSS applications.
基金National Natural Science Foundation of China (Grant Nos. 51835009, 52105116)China Postdoctoral Science Foundation (Grant Nos. 2021M692557, 2021TQ0263)。
文摘Deep learning(DL) is progressively popular as a viable alternative to traditional signal processing(SP) based methods for fault diagnosis. However, the lack of explainability makes DL-based fault diagnosis methods difficult to be trusted and understood by industrial users. In addition, the extraction of weak fault features from signals with heavy noise is imperative in industrial applications. To address these limitations, inspired by the Filterbank-Feature-Decision methodology, we propose a new Signal Processing Informed Neural Network(SPINN) framework by embedding SP knowledge into the DL model. As one of the practical implementations for SPINN, a denoising fault-aware wavelet network(DFAWNet) is developed, which consists of fused wavelet convolution(FWConv), dynamic hard thresholding(DHT),index-based soft filtering(ISF), and a classifier. Taking advantage of wavelet transform, FWConv extracts multiscale features while learning wavelet scales and selecting important wavelet bases automatically;DHT dynamically eliminates noise-related components via point-wise hard thresholding;inspired by index-based filtering, ISF optimizes and selects optimal filters for diagnostic feature extraction. It’s worth noting that SPINN may be readily applied to different deep learning networks by simply adding filterbank and feature modules in front. Experiments results demonstrate a significant diagnostic performance improvement over other explainable or denoising deep learning networks. The corresponding code is available at https://github. com/alber tszg/DFAWn et.
基金supported by the National Key R&D Program of China(No.2018YFD0901004)the National Natural Science Foundation of China(No.31601538)+2 种基金the Key Science and Technology Program of Liaoning Province(No.2020JH1/10200001)the Fundamental Research Foundation of Education Department of Liaoning Province(No.JL202008)the Science&Technology Innovation Foundation of Dalian(No.2019J12SN61).
文摘Heavy metal ions in shellfish products are harmful to human health,and their removal with low nutrient loss remains challenging.Herein,a new type of mesoporous silica(SBA15),modified internally with ammonium pyrrolidine dithiocarbamate(APDC)and externally with alkyl-diol groups,which was named as Diol-APDC-SBA15,was successfully developed and characterized by powder X-ray diffraction patterns,nitrogen adsorption,and Fourier transform infrared spectroscopy.The solutions with lead,chromium,cadmium,and copper were used to investigate the adsorption capacity of Diol-APDC-SBA15.Diol-APDC-SBA15 was adopted to remove heavy metals from cooking liquids of clams(Ruditapes philippinarum),hydrolysate liquids of oysters(Ostrea gigas Thunberg),and polysaccharide solution from the cooking liquid of R.philippinarum.The efficiencies of removing heavy metal ions and the loss rates of proteins and polysaccharides were examined.The results showed that the adsorption capacities of Diol-APDCSBA15 for Pb,Cr,Cd,and Cu in standard heavy-metal solutions were 161.4,166.1,29.6,and 60.2mgg^(−1),respectively.The removal efficiency of Diol-APDC-SBA15 for Pb in the three shellfish processing liquids ranged from 60.5%to 99.6%.The Cr removal efficiency was above 99.9%in the oyster hydrolysate liquid.Meanwhile,the percentages of polysaccharide loss were 5.5%and 3.7%in the cooking liquid of clam and polysaccharide solution,respectively,and the protein loss was 1.2%in the oyster hydrolysate liquid.Therefore,the Diol-APDC-SBA15 material exhibits a great potential application in the removal of heavy metals from shellfish processing liquids with low losses of proteins and polysaccharides.
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(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Part of the research leading to these results has received funding from the research project DESDEMONA–Detection of Steel Defects by Enhanced MONitoring and Automated procedure for self-inspection and maintenance (grant agreement number RFCS-2018_800687) supported by EU Call RFCS-2017sponsored by the NATO Science for Peace and Security Programme under grant id. G5924。
文摘Large structures,such as bridges,highways,etc.,need to be inspected to evaluate their actual physical and functional condition,to predict future conditions,and to help decision makers allocating maintenance and rehabilitation resources.The assessment of civil infrastructure condition is carried out through information obtained by inspection and/or monitoring operations.Traditional techniques in structural health monitoring(SHM)involve visual inspection related to inspection standards that can be time-consuming data collection,expensive,labor intensive,and dangerous.To address these limitations,machine vision-based inspection procedures have increasingly been investigated within the research community.In this context,this paper proposes and compares four different computer vision procedures to identify damage by image processing:Otsu method thresholding,Markov random fields segmentation,RGB color detection technique,and K-means clustering algorithm.The first method is based on segmentation by thresholding that returns a binary image from a grayscale image.The Markov random fields technique uses a probabilistic approach to assign labels to model the spatial dependencies in image pixels.The RGB technique uses color detection to evaluate the defect extensions.Finally,K-means algorithm is based on Euclidean distance for clustering of the images.The benefits and limitations of each technique are discussed,and the challenges of using the techniques are highlighted.To show the effectiveness of the described techniques in damage detection of civil infrastructures,a case study is presented.Results show that various types of corrosion and cracks can be detected by image processing techniques making the proposed techniques a suitable tool for the prediction of the damage evolution in civil infrastructures.
