Diffusion Stage Research Articles

Evaluations of Lagrangian egg drift models: From a laboratory flume to large channelized rivers

To help better interpret computational models in predicting drift of carp eggs in rivers, we present a series of model assessments for the longitudinal egg dispersion. Two three-dimensional Lagrangian particle tracking models, SDrift and FluEgg, are evaluated in a series of channels with increasing complexity. The model evaluation demonstrates that both models are able to accommodate channel complexity and provide a wide range of dispersion coefficients: Kl=O(1−100)Hu∗ with H being water depth and u∗ being shear velocity. In a straight channel with Kl=O(1)Hu∗, SDrift predicts weaker longitudinal dispersion than FluEgg in the early stage as a result of weak vertical mixing associated with smooth wall turbulence. With sufficient time, SDrift and FluEgg predict similar egg dispersion, accounting for the differential advection due to the vertical velocity profile. In an idealized curved channel with Kl=O(10)Hu∗, dispersion is driven by both vertical and transverse velocity profiles. SDrift yields slightly larger dispersion coefficients than FluEgg. In a real river with channel-training structures and having Kl=O(100)Hu∗, SDrift predicts a stronger longitudinal dispersion than FluEgg due to substantial local turbulent eddies and velocity gradients. To summarize, FluEgg shows good performance in capturing dispersion due to vertical velocity profiles and cross-channel velocity gradients. SDrift shows excellent model capabilities of revealing various dispersion mechanisms in addition to the vertical and cross-channel velocity variations. They include the initial turbulent diffusion stage with growing dispersion coefficients and strong dispersion due to in-stream hydraulic structures and localized turbulence.

Diffusion of Agricultural Technology Innovation: Research Progress of Innovation Diffusion in Chinese Agricultural Science and Technology Parks

With the rapid development of agricultural technology in China, a new model of agricultural technology diffusion, represented by agricultural science and technology parks, has been formed. We systematically sort out the progress of agricultural technology diffusion-related research based on a proposed research framework of technology diffusion in agricultural science and technology parks. The growth mechanism of agricultural technology poles, agricultural technology diffusion system, and its characteristics are analyzed. An index system of technology diffusion environment evaluation is summarized. From the perspective of the “basic” paradigm, we discuss the characteristics of the time process (diffusion stage, diffusion speed, diffusion breadth) and the spatial process (diffusion effect, spatial pattern) of technology diffusion in agricultural science and technology parks and their influence mechanisms. The fundamental law of “point-axis” diffusion of technology diffusion in the park is summarized. From the perspective of the “adoption” paradigm, we analyzed the influencing factors and mechanisms of farmers’ technology adoption. The effects of different environments and technologies with different attributes on farmers’ adoption behavior are explored. Based on the latest research results, we summarized new business agents’ technology adoption behaviors and mechanisms. Finally, we point out the issues that need to be further explored in studying the technology diffusion of agricultural innovations.

Measuring the Level of Regional Economic Synergistic Development and Its Driving Factors

ABSTRACT Using the case of 21 cities of Guangdong Province, China, this study uses the Harken model to evaluate the level of regional economic synergistic development from 2000 to 2019 and three economic synergistic development drivers, including comparative advantage, economic linkage, and industry. The study finds that the regional industrial division of labor is the main regional economic synergistic development driver in Guangdong. It also finds that the overall level of synergistic development has evolved from an intermediate diffusion stage to an advanced, symbiotic one. However, apparent differences exist in the gradient of the East Guangdong – West Guangdong – North Guangdong – Pearl River Delta. The results of this study and their implications are also explained.

Bibliometric Analysis of Interferometric Synthetic Aperture Radar (InSAR) Application in Land Subsidence from 2000 to 2021

Land subsidence is one of the serious natural disasters which can cause heavy casualties and economic losses. As a vital method, Interferometric Synthetic Aperture Radar (InSAR) can provide quick and efficient solutions for analysis. Currently, most reviews on InSAR application in land subsidence only focused on single types of land areas, such as the land around groundwater and land of the mining area. There is a lack of discussion on all types of land areas. This study thus aims at conducting a bibliometric literature analysis of the existing literature from 2000 to 2021 to fill this gap. The authors used scientific mapping methods to analyze the InSAR applications in land subsidence so that researchers and practitioners can comprehend the procedure. Then, the authors identified the major research areas, development milestones, evolutionary stages, and the transaction dynamics of evolutionary stages. Knowledge maps of five aspects were applied and analyzed in this research, including temporal development analysis, countries and institutions, major research disciplines, high-frequency terms, and cocitation of high-citation papers. The results reveal that the research of land subsidence monitoring with InSAR is in the stage of diffusion from developing many tools and techniques to integrating with other research areas. Overall, the bibliometric results combined with evolutionary stages provide a holistic picture of the status quo and future trends in InSAR application in land subsidence.

Characteristics of water migration during spontaneous imbibition in anisotropic coal

Spontaneous imbibition is a process of effectively wetting coal pores, which can improve wetting uniformity. Therefore, spontaneous imbibition is critical for outburst, dust and rockburst preventions. Due to the anisotropy of coal, water injected into the borehole has different wetting characteristics along different bedding directions. To reveal the characteristics of water migration in coal samples with different bedding directions during spontaneous imbibition, T2 spectrum and imaging images measured by nuclear magnetic resonance are comprehensively analyzed. The fracture presents the effects of huffing and puffing during spontaneous imbibition. However, the effects of huffing and puffing gradually decrease with increasing bedding angle. Imbibition equilibrium time increases with increasing bedding angles. The wetting effect of pores, liquidity and wetting uniformity of water gradually become poor with increasing bedding angles. Spontaneous imbibition process presents the Lucas-Washburn model, and the imbibition curve can be divided into spontaneous imbibition, transition and diffusion stages. The wetting time perpendicular to bedding direction, layout of water injection boreholes and gas drainage boreholes perpendicular to bedding direction should be fully considered to prevent wetting blank areas. This research reveals the wetting behaviors of anisotropic coal during imbibition and provides guidance for layout and optimization of coal seam water injection boreholes.

Time Series Analysis of Policy Discourse on Green Consumption in China: Text Mining and Network Analysis

Green consumption in China is a major promotion strategy for achieving sustainable development goals. It should be promoted from a long-term perspective based on cooperation from all levels of society. In addition, constantly revising the policy direction using policy discourse as feedback is necessary. This study analyzes policy discourse on green consumption in China from the long-term and time series perspectives. It employs text mining and network analysis by collecting Chinese online portal data on policy discourse over a period from 2000 to 2020. Using text mining, the study finds that green consumption develops through four stages, namely awareness, practice, diffusion, and social responsibility. From a long-term perspective, policymaking and the preparation of government guidelines take place during the awareness stage, the distribution of action plans and related guidelines from central to local governments takes place in the practice stage, and participation in green consumption in the different classes of society occurs in the diffusion stage. The conscious transition to green consumption by the government, the business sector, and the public can be found in the social responsibility stage. The results of the convergence of iterated correlation analysis reveal that policy discourse on green consumption initially transitions from a specific to a diversified topic. This means that, since there are many complex policy and social issues related to green consumption, it is necessary to select and focus on appropriate topics when setting policy directions. Lastly, core–periphery analysis indicates that growers related to global environmental issues, such as carbon neutrality and climate change, are leading green consumption in China. This confirms that green consumption is a key issue that the government and the public must practice to support the sustainable development of mankind, transcending constraints of time, space, class, and ideology. On the basis of its results, the study proposes a development strategy that can strike a balance between the universality and specificity of green consumption in China.

In-silico study about the influence of electroporation parameters on the chemotherapeutic drug transport in cancer tissues using the meshless method of approximate particular solutions

Electroporation has become an important technique in cancer treatment to induce the drug internalization into cells by applying controlled electric pulses. In the present work, the simulation of transport of two chemotherapeutic drugs (doxorubicin and cisplatin) in electroporated cancerous tissues is carried out using the Global Method of Approximate Particular Solutions (Global MAPS), which is a meshless method having several computational advantages over finite element and finite volume methods commonly used in this kind of problems. Numerical parameters involved in Global MAPS simulations are calibrated by means of validation with results previously published in literature, points-number and time-step dependency analyses, and convergence analysis on a relaxation factor, obtaining satisfactory results. Voltage levels of 300 V, 350 V and 400 V, and pulse spacing of 10 s, 100 s and single pulse are considered as input electroporation parameters, whose influence on the following variables is analyzed: magnitude and distribution of electric field in the pulse stage; extracellular and intracellular concentrations of medicament in the pre-pulse and post-pulse diffusion stages, identifying different transport mechanism (internalization and extracellular diffusion) and the concentration equilibrium condition when reached; and efficiency and aggressiveness of the electroporation protocol. In general, numerical results point out that this influence highly depends on the drug type used during the electrochemotherapy treatment. • Transport simulation of drugs in electroporated cancer tissues using meshless technique. • Influence of voltage and pulse spacing on electric field, extracellular and intracellular concentrations. • Influence of voltage and pulse spacing on efficiency and aggressiveness of electroporation protocol. • Differences between cisplatin and doxorubicin behavior in pre-pulse and post-pulse diffusion stages. • Study of main transport mechanisms and concentration equilibrium condition for both drugs.

Ultrasound-Assisted Extraction of β-Asarone from Sweet Flag (Acorus calamus) Rhizome

In this study, the extraction efficiency of β-asarone from Malaysian Acorus calamus from Acoraceae family using conventional solvent extraction and ultrasound-assisted extraction techniques was compared. The results showed that the ultrasound-assisted extraction technique significantly improves the extraction yields and process feasibility without changing the structure of the active compound, i.e., β-asarone. The extraction yield increment was found to be ~2.5-fold and ~1.6-fold at 1:100 and 1:50 solid-to-solvent ratio, at 30% applied sonication power. The positive impact of sonication can also be observed for both mechanistic stages of extraction, i.e., the washing and diffusion stages, due to the favorable physical effect of acoustic cavitations. The observation was supported by the SEM images of the plant residue. The characterization of the extract was carried out using HPLC, NMR, UV and IR techniques. In conclusion, ultrasound assistance increases the extraction efficiency by ~2.5-fold even at only 30% applied ultrasonic power at a 1:100 solid-to-solvent ratio. The present study also provides an efficient and simple method for accurate direct dosing of Acorus calamus extracts to an application.

Fast quantum image encryption scheme based on multilayer short memory fractional order Lotka-Volterra system and dual-scale triangular map

The Caputo fractional order Lotka-Volterra system is time-consuming in practical applications, since its starting point is fixed. To tackle this problem, a short memory fractional order Lotka-Volterra system (SMFrLVS) is proposed, where the chaotic attractor of the short memory fractional order Lotka-Volterra system is achieved by the predictor-corrector method. Then, a multilayer fractional order Lotka-Volterra system with short memory (MSMFrLVS) is introduced, whose chaotic behaviors are explored via Poincare sections and frequency power spectra. A quantum image encryption algorithm is proposed by combining MSMFrLVS with quantum dual-scale triangular map. A quantum circuit of the dual-scale triangular map is designed with ADDER-MOD2n. At the permutation stage, the plaintext image is transformed into quantum form with the generalized quantum image representation model. The resulting quantum image is divided into sub-blocks and scrambled by the quantum dual-scale triangular map. Subsequently, the intra and the inter permutation operations on bit-planes are realized by sorting pseudo-random sequence and by quantum Gray code, respectively. At the diffusion stage, the initial values of the MSMFrLVS are generated with a plaintext correlation mechanism. The ciphertext image can be acquired by carrying out three-level diffusion operations. It is demonstrated that the proposed quantum image encryption algorithm performs better than some typical image encryption algorithm in terms of security, robustness, computational complexity and encryption speed.

An Efficient Lightweight Image Encryption Scheme Using Multichaos

With an immense increase in Internet multimedia applications over the past few years, digital content such as digital images are stored and shared over global networks, the probability for information leakage and illegal modifications to the digital content is at high risk. These digital images are transferred using the network bandwidth; therefore, secure encryption schemes facilitate both information security and bandwidth issues. Hence, a state-of-the-art lightweight information security methodology is required to address this challenge. The main objective of this work is to develop a lightweight nonlinear mechanism for digital image security using chaos theory. The proposed scheme starts by changing a plain image into an encrypted image to improve its security. A block cipher, using lightweight chaos, has been added to achieve this objective for digital image security. We utilized multiple chaotic maps to generate random keys for each channel. Also, Arnold cat map and chaotic gingerbread map are used to add confusion and diffusion. During the permutation stage, image pixels are permuted, while in diffusion stage, pixels are distorted utilizing gingerbread map to add more security. The proposed scheme has been validated using different security parameter tests such as correlation coefficient tests (CC), whose results have been observed closer to zero and information entropy (IE) value is 7.99, respectively, which is almost equal to the ideal value of 8. Moreover, number of pixels changing rate (NPCR) obtained value is higher than 99.50%, while the unified average changing intensity (UACI) is 33.33. Other parameters such as mean absolute error (MAE), mean square error (MSE), lower value of peak to signal noise ratio (PSNR), structural content (SC), maximum difference (MD), average difference (AD), normalized cross-correlation (NCC), and histogram analysis (HA) is tested. The computed values of the proposed scheme are better. The achieved results after comparison with existing schemes highlight that the proposed scheme is highly secure, lightweight, and feasible for real-time communications.

A Forward Identification Method for High-Temperature Stress–Strain Curves of 7075 Aluminum Alloy Sheet Considering the Necking Stage

The necking phenomenon of metal sheet under high temperatures is serious and continues over a longer duration. It is difficult to describe the high-temperature mechanical properties of materials only on the basis of hardening behavior before necking. To obtain the high-temperature stress–strain curve considering diffuse necking stage, a forward identification method based on strain measurement is proposed in this study. Here, the strain field of the minimum cross-section in the necking region of the specimen is obtained using a DIC (digital image correlation) measurement technique, and the average axial true stress–strain curve is calculated. Then, the average axial true stress–strain curve is modified using the modified Bridgeman formula. Taking 7075 aluminum alloy as an example, the high temperature equivalent stress–strain curve considering the diffuse necking stage is obtained. Compared with the traditional method, the maximum effective strain range is expanded from 0.05 to 0.8 due to the consideration of the necking stage. The obtained curve is characterized by a coupled viscoplastic–damage constitutive model and embedded in ABAQUS through the user subroutine VUMAT to simulate the hot tensile process. The relative error of force–displacement between the simulation and the experiment was 2.4%, validating the ability of the presented method. This study provides theoretical guidance and a scientific basis for the application and forming control of hot stamping processes.

Study of turbulent dispersion of a concentration plume emitting from a line source over a rib‐roughened surface

Turbulent dispersion of a concentration plume emitting from a horizontal line source over a rib-roughened surface has been studied using direct numerical simulations (DNS). Four test cases have been compared to investigate the effects of the source elevation and location on the plume dispersion in a turbulent boundary layer. The transport process of the concentration is investigated in both physical and spectral spaces which includes analyses of statistical moments of the concentration field, decay rate, plume width, pre-multiplied spectra of the velocity and concentration fields, and the probability density function (PDF) of concentration fluctuations. It is observed that as the mean plume development enters the long-range dispersion stage, the decay rate of the mean concentration field begins to feature a constant slope of −3/2, while the vertical spread of the mean plume exhibits a constant slope of 1/3 in all four line source release cases in a ribbed wall flow. It is also observed that the profiles of both the mean concentration field and the RMS of concentration fluctuations exhibit a self-similarity pattern downstream of the line source in all four test cases. By comparing the characteristic length scales of the spanwise velocity and scalar fields, two distinct stages of the instantaneous plume development are observed, dominated by the turbulent convective and diffusive mechanisms. It is discovered that the transition from the turbulent convective stage to the turbulent diffusive stage occurs more rapidly for line sources placed near the wall and inside the cavities.

Atomic-level sintering mechanism of silica aerogels at high temperatures: structure evolution and solid thermal conductivity

Silica aerogels are extensively used for thermal insulation at high temperatures. However, it has been experimentally found that high temperature can change the pore structure and undermine thermal insulation. The mechanism of high temperature influence is unclear due to the limited resolution of experimental observations. In the present work, molecular dynamics simulations and theoretical modeling were combined to investigate the effects of high temperature on pore structures and heat conduction. At the scale of nanoparticles, the structural evolution induced by the sintering process of silica aerogels was numerically investigated. The melting process of a single silica nanoparticle can be divided into three stages, and it was found that extending the stage of surface diffusion can improve the thermal stability of silica nanoparticles. At the scale of particle assembly, the contact diameter between adjacent particles was identified and numerically evaluated. At the scale of bulk material, a theoretical model was developed to predict the solid thermal conductivity by considering both the temperature effect on the intrinsic thermal conductivity of backbone and the effect of nanoparticle size. A good agreement was found between the present model and available experimental data. An insightful discussion of the existing theoretical models and experimental data was also presented. The present work can inspire further cross-scale modeling of silica aerogels and may pave the way for the development of silica aerogels with high stability and thermal insulation at high temperatures.

Dynamic modeling of biotechnology adoption with individual versus social learning: An application to US corn farmers

AbstractRelative roles of individual versus social learning on biotechnology adoption are investigated with an empirical focus on the adoption of Genetically Modified (GM) corn in the US Corn Belt. Relying on a Kalman filter algorithm, the unobservable learning process is parameterized in a dynamic programming problem, and parameters are estimated using a minimum‐distance estimator. Estimates show that farmers are risk‐averse and that both individual and social learning affect GM technology adoption with more importance on individual learning than social learning, whose statistical significances are confirmed by hypothesis testing. Sensitivity analysis results show that social learning contributes to lower GM adoption rates, reflecting a strategic delay in the presence of information externalities in the early and middle diffusion stages. [EconLit Citations: C61, D83, O33].

A coupling study of ignition position on fuel-air mixing and diffusion of a linear hydrogen engine

Linear hydrogen engine (LHE) is a new technology of hydrogen energy utilization due to its flexible compression ratio coupling with ignition, fuel-air mixing, and combustion to optimize thermal efficiency. Fuel-air mixing in LHE is expected to be promoted by using ignition, which differs with conventional engine. This paper develops a full-cycle model which couples with dynamics, hydrogen-air mixing and combustion to describe the effect of ignition position, meanwhile a loop iterative calculation method is proposed to solve the coupling model for hydrogen-air mixing predication. The results show that ignition position variation can cause the piston trajectory to change significantly, and the higher equivalent speed is obtained in the medium ignition position. Besides, the higher equivalent speed in the injection stage is conducive to the diffusion of hydrogen, but the higher equivalent speed is not conducive to diffusion and mixing in the diffusion stage. More importantly, the equivalence ratio distribution at the ignition position is more uniform for the later ignition position due to the longer mixing stroke, and the mixture uniformity index at the ignition position is inversely proportional to the advance of the ignition position. Therefore, the late ignition is recommended to obtain a uniform hydrogen mixture.

Effect of 4-Hydroxy-l-proline-containing podands on the stereoselectivity of Biginelli reaction according to molecular dynamics

The synthesis and theoretical study of the stereoselectivity of Biginelli reaction with chiral inductors based on 4-hydroxy-l-proline podands with four oxyethylene moieties have been performed. The predominant formation of the iminium intermediate during the interaction of the podand salt form with benzaldehyde was experimentally shown. Metadynamic simulation of reaction mixture with 4-hydroxy-l-proline-containing podand in salt and base forms allowed us to compare the probability of reactants approach from re- and Si-sides on the diffusion stage. We modeled the arrangement of reactants in the pre-reactional stage of alternative steps that could have a key effect on enantiomeric excess of 1,4-dihydropyrimidinone. Results showed that the interaction of a podand-acetoacetate adduct with N-benzylideneurea was preferred, when the podand was in a base form, while for a salt form, the intereaction with benzaldehyde was more favorable, which led to higher stereoselectivity. The effect of intermolecular interactions on the stabilization of prereaction states was analyzed.

Crossing the valley of death: Network structure, government subsidies and innovation diffusion of industrial clusters

To successfully cross the “valley of death” between source innovation and industrialization requires two-way efforts of technological innovation and innovative achievement transformation, which is a socialization process of innovation adoption and diffusion. Industrial clusters are the effective organizational carriers for the diffusion of innovation achievements, therefore, the research aims to explore the transformation mechanism of scientific and technological achievements in industrial clusters, especially considering the influence of network structure and government subsidies in helping industrial clusters to cross the valley of death and improve the efficiency of scientific and technological achievements transformation, so as to put forward targeted transformation countermeasures. Accordingly, a “two-stage and double-driving” innovation diffusion dynamics model was built and applied to the empirical research on China's blockchain industrial cluster by network analysis and system dynamics. It is found that government subsidies play a crucial role in the innovation adoption stage, especially for high innovative industrial clusters. In addition, there is an adoption threshold for the utility of government subsidies, and a reasonable exit mechanism should be established when adoption rates reach a certain proportion. However, for the low innovative industrial clusters, government subsidies continue to be effective. On the contrary, internal factors play a vital role in the stage of innovation diffusion, especially for industrial clusters that have developed close cooperation between upstream and downstream. This study provides the following policy implications for industrial clusters to overcome the valley of death, including carrying out classified guidance and precise implementation, appropriate subsidies and reasonable withdrawal, and improving the cultivation mechanism of “opinion leaders” enterprises.

Pollutant Migration Pattern during Open-Pit Rock Blasting Based on Digital Image Analysis Technology

Previous studies have revealed that toxic gases and dust (smoke dust) are the most common pollutants generated by the blasting operations in open-pit mines, which might lead to a threat to the environment’s condition, health and safety, and properties protection around the blasting site. In order to deal with the problems, a pollution evaluation system was established based on the fractal dimension theory (Dbox(P)) and grayscale average algorithm (Ga) in digital image-processing technology to recognize and analyze the distributions of the smoke-dust cloud, and subsequently determine the pollution degrees. The computation processes of Dbox(P) and Ga indicate three fitted correlations between the parameters and diffusion time of smoke dust. Then, a pollution index (Pi) is put forward to integrate the global and local features of Dbox(P) and Ga, and develop a hazard classification mechanism for the blasting pollutants. Results obviously denote three diffusion stages of the pollutants, mainly including generation stage, cloud-formation stage, and diffusion stage. In addition, it has been validated that the proposed system can also be utilized in single-point areas within a whole digital image. Besides, there are variation trends of the thresholds T1 and T2 in binarization with the diffusion of pollutants. With this identification and evaluation system, the pollution condition of smoke dust can be obviously determined and analyzed.

An Image Encryption Algorithm Based on Complex Network Scrambling and Multi-Directional Diffusion.

Various security threats are encountered when keys are transmitted in public channels. In this paper, we propose an image encryption algorithm based on complex network scrambling and multi-directional diffusion. Combining the idea of public key cryptography, the RSA algorithm is used to encrypt the key related to plaintext. The algorithm consists of three stages: key generation stage, complex network scrambling stage, and multi-directional diffusion stage. Firstly, during the key generation phase, SHA-512 and the original image are used to generate plaintext-related information, which is then converted to plaintext-related key through transformation mapping. Secondly, in the complex network scrambling stage, the chaotic random matrix establishes the node relationships in the complex network, which is then used to construct an image model based on the complex network, and then combines pixel-level and block-level methods to scramble images. Finally, in the multi-directional diffusion stage, the multi-directional diffusion method is used to perform forward diffusion, middle spiral diffusion, and backward diffusion on the image in turn to obtain the final ciphertext image. The experimental results show that our encryption algorithm has a large keyspace, the encrypted image has strong randomness and robustness, and can effectively resist brute force attack, statistical attack, and differential attack.

Nanocarriers for combating biofilms: Advantages and challenges.

Bacterial biofilms are highly resistant to antibiotics and pose a great threat to human and animal health. The control and removal of bacterial biofilms have become an important topic in the field of bacterial infectious diseases. Nanocarriers show great anti-biofilm potential because of their small particle size and strong permeability. In this review, the advantages of nanocarriers for combating biofilms are analysed. Nanocarriers can act on all stages of bacterial biofilm formation and diffusion. They can improve the scavenging effect of biofilm by targeting biofilm, destroying extracellular polymeric substances and enhancing the biofilm permeability of antimicrobial substances. Nanocarriers can also improve the antibacterial ability of antimicrobial drugs against bacteria in biofilm by protecting the loaded drugs and controlling the release of antimicrobial substances. Additionally, we emphasize the challenges faced in using nanocarrier formulations and translating them from a preclinical level to a clinical setting.