Diffusion Speed Research Articles

The paradox of product scarcity: Catalyzing the speed of innovation diffusion

AbstractProduct shortages are known to slow down the diffusion process. However, we counterintuitively theorize and empirically demonstrate that under specific conditions of social influence, the diffusion process may be accelerated by early product scarcity. Using an Agent-Based framework and Genetic Algorithm-based estimation, we analyzed 20 product categories to identify the critical trade-off influencing diffusion: the interplay of the social influence ratio of waiting customers to adopters, the external influence, and level of product scarcity. Strategic managerial actions can accelerate the adoption of products. For example, in the case of fitness trackers, we were able to simulate speed-up by up to two years compared to the standard Bass model. Importantly, we introduce a novel framework to study competition dynamics, analyzing how the timing of market entry and the production capacity of competitors, along with the initial installed capacity of the pioneering firm affect diffusion speed. This acceleration, whether due to managerial foresight or serendipity, necessitates careful orchestration to harness the enthusiasm of waiting customers and strategically allocate marketing spending on social media platforms, thereby differentially amplifying the influence of adopters and potential customers.

Exploring the spatial effects influencing the EGFR/ERK pathway dynamics with machine learning surrogate models

The fate of cells is regulated by biochemical reactions taking place inside of them, known as intracellular pathways. Cells display a variety of characteristics related to their shape, structure and contained fluid, which influences the diffusion of proteins and their interactions. To gain insights into the spatial effects shaping intracellular regulation, we apply machine learning (ML) to explore a previously developed spatial model of the epidermal growth factor receptor (EGFR) signaling. The model describes the reactions between molecular species inside of cells following the transient activation of EGF receptors. To train our ML models, we conduct 10,000 numerical simulations in parallel where we calculate the cumulative activation of molecules and transcription factors under various conditions such as different diffusion speeds, inactivation rates, and cell structures. We take advantage of the low computational cost of ML algorithms to investigate the effects of cell and nucleus sizes, the diffusion speed of proteins, and the inactivation rate of the Ras molecules on the activation strength of transcription factors. Our results suggest that the predictions by both neural networks and random forests yielded minimal mean square error (MSEs), while linear generalized models displayed a significant larger MSE. The exploration of the surrogate models has shown that smaller cell and nucleus radii as well, larger diffusion coefficients, and reduced inactivation rates increase the activation of transcription factors. These results are confirmed by numerical simulations. Our ML algorithms can be readily incorporated within multiscale models of tumor growth to embed the spatial effects regulating intracellular pathways, enabling the use of complex cell models within multiscale models while reducing the computational cost.

Different effects of cardiomyocyte contractile activity on transverse and axial tubular system luminal content dynamics

BackgroundEfficient excitation-contraction coupling of mammalian ventricular cardiomyocytes depends on the transverse − axial tubular system (TATS), a network of surface membrane invaginations. TATS enables tight coupling of sarcolemmal and sarcoplasmic reticulum membranes, which is essential for rapid Ca2+-induced Ca2+ release, and uniform contraction upon electrical stimulation. The majority of TATS in healthy ventricular cardiomyocytes is composed of transverse tubules (TT, ~90 % of TATS in rabbit). The remainder consists of mostly axial tubules (AT), which are less abundant and less well studied. In disease, however, the relative abundance of TT and AT changes. The mechanisms and relevance of this change are not known, and understanding them requires a more targeted effort to study the dynamics of AT structure and function.While TATS content is continuous with the interstitial space, it is contained within a domain of restricted diffusion. We have previously shown that TT are cyclically squeezed during stretch and contraction. This can contribute to TT content mixing and accelerates luminal content exchange with the environment. Here, we explore the effects of cardiomyocyte stretch and contraction on AT. MethodsTATS structure and diffusion dynamics were studied using 3D electron tomography of rabbit left ventricular cardiomyocytes, preserved at rest or during contraction, and ventricular tissue preserved at rest or during stretch, as well as live-cell TATS content exchange measurements. ResultsWe show (i) that cardiomyocyte contraction is associated with an increase in the apparent speed of diffusion of TT content that scales with beating rate and degree of cell shortening. In contrast, (ii) AT develop membrane folds and constrictions during contraction, (iii) with no effect of contraction on luminal exchange dynamics, while (iv) cardiomyocyte stretch is associated with AT straightening and AT and TT ‘squeezing’ that (v) supports an acceleration of the apparent speed of diffusion in AT and TT. Finally, (vi) we present a simple computational model outlining the potential relevance of AT in healthy and diseased cells. ConclusionsOur results indicate that TT and AT are differently affected by the cardiac contractile cycle, and suggest that AT may play a role in ensuring TATS network content homogeneity in diseased cardiomyocytes. Further research is needed to explore the interplay of structural and functional remodelling of different TATS components in failing myocardium.

Exploring the patterns of China's carbon neutrality policies

To achieve the ambitious carbon neutrality goal by 2060, the Chinese government has implemented a series of carbon neutrality policies. These policy documents are pivotal in facilitating the examination of policy substance, the scrutiny of policy evolution, and the dissection of the policy instruments involved. This study develops an analytical framework for assessing carbon neutrality through policy documents, applying text mining and network analysis to probe the intricacies of policy topics, interagency collaboration, and diffusion dynamics. This research aims to delineate and expound upon the strategic paradigms employed by the Chinese government in its quest for carbon neutrality. The findings reveal a constellation of eleven policy topics, with "green" and "low carbon" being key aspects of each. The policy collaboration network has a density of 0.593, and the National Development and Reform Commission (NDRC)'s high average weighted degree of 14.6 highlights its crucial role in leading and coordinating these policies. In terms of diffusion dynamics, the green energy transition topic has a diffusion speed of 0.967 and a strength of 49, indicating its importance to the Chinese government. On a practical level, the findings offer policy-makers concrete, actionable recommendations to refine policy design and enhance implementation effectiveness. Theoretically, this study advances the scientific understanding of policy dynamics by proposing a novel analytical framework that integrates multiple dimensions of policy analysis, contributing to the methodological development of policy research.

Development of Polyvinyl Alcohol Hydrogels for Controlled Glucose Release in Biomedical Applications.

Polyvinyl alcohol (PVA) hydrogels have a wide range of applications in the pharmaceutical and biomedicine fields due to their exceptional biophysical properties. The study focuses on preparing and characterizing capsule-shaped PVA hydrogels to enhance their biocompatibility and porosity for controlled glucose release and cell proliferation. The hydrogels were prepared using different concentrations (Cs) and molecular weights (MWs) of PVA, with two different lengths, A (10 mm) and B (20 mm), to control glucose release over 60 min. The preparation process involved PVA gel preparation and PVA hydrogel formation. A total of 500 µL of glucose was injected into all dehydrated hydrogels in groups A and B. Glucose release was studied by immersing the hydrogels in saline at 37 °C with stirring at 500 rpm. The SUP-B15 cell line was grown in six A1 hydrogels for biocompatibility testing. The results indicate that all hydrogels remained stable at 37 °C without degrading. Those with a higher C and MW exhibited a denser and less porous structure, lower glucose storage capacity, and higher elongation at break. Significant differences in glucose release, diffusion speed, and flux were observed, which were more evident in A1 > A4, B1 > B4, and B1 > A1 over 60 min. A1 and B1 had higher values because their higher porosity distribution allowed glucose to diffuse more easily. B1, being larger, has more glucose due to its increased length. The cell growth response and viability at 48 h in contact with the hydrogels was similar to that of the control (4.5 × 105 cells/mL, 98.5% vs. 4.8 × 105 cells/mL, 99.7% viability), thus demonstrating biocompatibility. The hydrogels effectively released glucose over 60 min, with variations based on porosity, C, MW, and length, and demonstrated good biocompatibility with the cell line.

Time is the enemy: The speed of proximity‐based knowledge diffusion

AbstractDoes knowledge spread more quickly when firms are geographically closer? Focusing on knowledge diffusion from multinational enterprises (MNEs) subsidiaries in the context of the US semiconductor industry, our analysis suggests that the broader MNE patents are, in terms of the knowledge sources they draw on, the slower the speed of knowledge diffusion to more spatially proximate firms, compared to more distant ones. Moreover, our findings suggest that this outcome could be attributed to a greater reliance on knowledge sources that are internal to the MNE network or located geographically distant. We provide interpretative cues for these findings and provide policy recommendations in line with our results.

Study of arc and magnetic field parameters under delayed breaking condition of DB-DC VCB

Taking the mechanical double-break DC vacuum circuit breaker (DB DC VCB) as the research object, the magnetic field and temperature field distribution between the breaks and the plasma characteristics under the working condition of gap difference caused by actuator dispersion are investigated to explore the difference in arc characteristics between the two breaks. Based on the system of Maxwell and magnetohydrodynamic (MHD) equations, a non-simultaneous breaking model of the DB DC VCB is established, and parameters such as magnetic flux density, plasma velocity, inter-contact pressure, and ion and electron temperatures are calculated. The simulation results show that the cathode surface field emission effect is stronger in the small gap break (delayed breaking break). Besides, in the small gap break, the arc temperature is higher, the rate of decrease of temperature is lower, the electron velocity is higher, the magnetic flux density is lower, the regulatory ability of the magnetic field is weaker, and the plasma diffusion speed is slower. In the arc ignition stage, the arc aggregation state duration of the small gap break is longer than that of the normal break, which means the arc in the small gap break gets diffused and arc energy dissipation becomes harder. Therefore, the arc energy density of the delayed breaking break is greater, the arc morphology transition time is longer, the residual particle concentration after arc extinguishing is higher, and the probability of re-strike breakdown increases with the increase in gap difference. Improving the synchronization of the actuator could improve the breaking ability of the DB DC VCB. Index terms—plasma arc, double-break direct current vacuum circuit breaker (DB-DC VCB), transverse magnetic field (TMF), magnetohydrodynamic (MHD) model.

Radiation Hydrodynamic Simulations of Massive Stars in Gas-rich Environments: Accretion of AGN Stars Suppressed by Thermal Feedback

Massive stars may form in or be captured into active galactic nuclei (AGN) disks. Recent 1D studies employing stellar-evolution codes have demonstrated the potential for rapid growth of such stars through accretion up to a few hundred solar masses. We perform 3D radiation hydrodynamic simulations of moderately massive stars’ envelopes in order to determine the rate and critical radius R crit of their accretion process in an isotropic gas-rich environment in the absence of luminosity-driven mass loss. We find that in the “fast-diffusion” regime where characteristic radiative diffusion speed c/τ is faster than the gas sound speed c s , the accretion rate is suppressed by feedback from gravitational and radiative advection energy flux, in addition to the stellar luminosity. Alternatively, in the “slow-diffusion” regime where c/τ < c s , due to adiabatic accretion, the stellar envelope expands quickly to become hydrostatic and further net accretion occurs on thermal timescales in the absence of self-gravity. When the radiation entropy of the medium is less than that of the star, however, this hydrostatic envelope can become more massive than the star itself. Within this subregime, the self-gravity of the envelope excites runaway growth. Applying our results to realistic environments, moderately massive stars (≲100M ⊙) embedded in AGN disks typically accrete in the fast-diffusion regime, leading to a reduction of steady-state accretion rate 1–2 orders of magnitudes lower than expected by previous 1D calculations and R crit smaller than the disk scale height, except in the opacity window at temperature T ∼ 2000 K. Accretion in slow diffusion regime occurs in regions with very high density ρ ≳ 10−9 g cm−3, and needs to be treated with caution in 1D long-term calculations.

The international dissemination of China’s English academic journals on Twitter: Structure, theme and impact

Objective/Significance: To measure the international communication capacity of China’s English academic journal papers based on social media platforms. Method/Process: Social network analysis, content analysis and emotion analysis were used to describe the diffusion structure of China’s English academic journal papers on Twitter from the aspects of network structure and identify important node users, explore the identity characteristics and emotion characteristics of users as well as diffusion capability of journals of different disciplines. Conclusion/Discovery: Journal articles in the fields of natural sciences and engineering as well as humanities and social sciences exhibit a strong positive correlation between their diffusion structure and network size. Networks with a mixed diffusion structure typically have larger network sizes. The users occupying key positions in the diffusion network typically have profile information that is academically relevant. The retweets and comments are mainly statements without emotional inclination, and the comments are mainly summary descriptions of the papers. The distribution of diffusion width, diffusion strength and diffusion speed of each discipline is significantly different. There is a significant positive correlation between the diffusion structure of papers and their diffusion capabilities. Innovation/Value: To reveal the diffusion structure and characteristics of China’s English academic journal papers on social media platforms, so as to provide reference for expanding the visibility of China’s English academic journals and improving the international dissemination capacity of China’s English journals.

Preliminary compact torus injection experiments on the Keda Torus eXperiment reversed field pinch

A new compact torus injector (KTX-CTI) has been built for injection experiments on the Keda Torus eXperiment (KTX) reversed field pinch (RFP). The aim is to study the fundamental physics governing the compact torus (CT) central fueling processes. In experiments conducted under the sole influence of a 0.1 T toroidal magnetic field, the injected CT successfully penetrated the entire toroidal magnetic field, reaching the inner wall of the KTX vacuum vessel. Upon reaching the inner wall, the CT diffused both radially outward and toroidally within the vessel at a discernible diffusion speed. Moreover, the inherent helicity within the CT induced a modest KTX plasma current of 200 A, consistent with predictions based on helicity conservation. CT injection demonstrated the capability to initiate KTX discharges at low loop voltages, suggesting its potential as a pre-ionization and current startup technique. During RFP discharges featuring CT injection, the central plasma density was found to exceed the Greenwald density limit, with more peaked density profiles, indicating the predominant confinement of CT plasma within the core region of the KTX bulk plasma.

Phylogenetic biogeography inference using dynamic paleogeography models and explicit geographic ranges.

To model distribution ranges, the most popular methods of phylogenetic biogeography divide Earth into a handful of predefined areas. Other methods use explicit geographic ranges, but unfortunately, these methods assume a static Earth, ignoring the effects of plate tectonics and the changes in the landscape. To address this limitation, I propose a method that uses explicit geographic ranges and incorporates a plate motion model and a paleolandscape model directly derived from the models used by geologists in their tectonic and paleogeographic reconstructions. The underlying geographic model is a high-resolution pixelation of a spherical Earth. Biogeographic inference is based on diffusion, approximates the effects of the landscape, uses a time-stratified model to take into account the geographic changes, and directly integrates over all probable histories. By using a simplified stochastic mapping algorithm, it is possible to infer the ancestral locations as well as the distance traveled by the ancestral lineages. For illustration, I applied the method to an empirical phylogeny of the Sapindaceae plants. This example shows that methods based on explicit geographic data, coupled with high-resolution paleogeographic models, can provide detailed reconstructions of the ancestral areas but also include inferences about the probable dispersal paths and diffusion speed across the taxon history. The method is implemented in the program PhyGeo.

A novel multi-frame image super-resolution model based on regularized nonlinear diffusion with Caputo time fractional derivative

In this work, we introduce an innovative fractional nonlinear parabolic model using a time-fractional order derivative, specifically employing the Caputo sense for fractional differentiation. This model aims to enhance traditional super-resolution models, particularly in the context of multi-frame image super-resolution. Additionally, we incorporate a regularized Perona–Malik diffusion mechanism to control the speed and direction of diffusion at each image location. We begin our study by exploring the theoretical solvability of our proposed model. Firstly, we employ the Faedo–Galerkin approach to establish the existence and uniqueness of a weak solution for an auxiliary fractional super-resolution model. Subsequently, we use the Schauder fixed point method to demonstrate the existence and uniqueness of a weak solution for our model. To validate the effectiveness of our model in the multi-frame super-resolution (SR) context, we conduct numerical experiments on images featuring diverse characteristics, including corners and edges, while applying various warping, decimation, and blurring matrices to the low-resolution (LR) images. We start the evaluation by introducing an adaptive discrete scheme tailored to the proposed model. To prove the robustness of our approach, we subject our images to varying levels of noise. Additionally, we perform simulations on real data (videos). The obtained high-resolution (HR) results demonstrate notable efficiency and robustness against noise, outperforming competitive models both visually and quantitatively.

Image inpainting algorithm based on double curvature-driven diffusion model with P-Laplace operator.

The method of partial differential equations for image inpainting achieves better repair results and is economically feasible with fast repair time. Addresses the inability of Curvature-Driven Diffusion (CDD) models to repair complex textures or edges when the input image is affected by severe noise or distortion, resulting in discontinuous repair features, blurred detail textures, and an inability to deal with the consistency of global image content, In this paper, we have the CDD model of P-Laplace operator term to image inpainting. In this method, the P-Laplace operator is firstly introduced into the diffusion term of CDD model to regulate the diffusion speed; then the improved CDD model is discretized, and the known information around the broken region is divided into two weighted average iterations to get the inpainting image; finally, the final inpainting image is obtained by weighted averaging the two image inpainting images according to the distancing. Experiments show that the model restoration results in this paper are more rational in terms of texture structure and outperform other models in terms of visualization and objective data. Comparing the inpainting images with 150, 1000 and 100 iterations respectively, Total Variation(TV) model and the CDD model inpainting algorithm always has inpainting traces in details, and TV model can't meet the visual connectivity, but the algorithm in this paper can remove the inpainting traces well, TV model and the CDD model inpainting algorithm always have inpainting traces in details, and TV model can't meet the visual connectivity, but the algorithm in this paper can remove the inpainting traces well. Of the images used for testing, the highest PSNR reached 38.7982, SSIM reached 0.9407, and FSIM reached 0.9781, the algorithm not only inpainting the effect and, but also has fewer iterations.

Particle Matter determination in Biosimilar Parenteral Product by the Application of Dynamic Light Scattering (DLS) Followed by Statistical Evaluation

Particulate matter in parenteral dosage forms can emerge from numerous causes, external, intrinsic, as well as inherent within the product, with a special emphasis on biopharmaceuticals. Aqueous impurities, pharmaceutical precipitates, dirt, glass, rubber, pollutants from the environment, fibres, and various other insoluble materials are all common sources of particulates. When assessing the possible harm to patients, particulate matter size is a crucial issue to consider. Particles as fine as 2 μm overall diameter were found related with microthrombi development. The DLS (Dynamic Light Scattering) technique has been used to measure and control the subvisible particulate particles in biopharmaceutical parenteral drug products since the technique can measure the submicron particle size in the parenteral formulation. The purpose of using DLS is to measure and control the subvisible particles in a biopharmaceutical formulation. A generic biopharmaceutical product viz. Calcitonin Salmon injection was used for particulate matter analysis by using Dynamic Light Scattering. DLS is a non-invasive method for detecting the size of suspended particles as well as molecules which is used for the control and optimization of processes, and the improvement of product quality and performance by analysing the time-dependence in regard to intensity of the dispersed light (auto correlation) to determine the diffusion speed (Brownian motion) of particles/molecules, and subsequently determine the hydrodynamic size. Keywords: Particulate matter; DLS; Biosimilars; Parenteral dosage forms

Revealing the superior rate performance and cycle stability of the La and F Co-doping LiFePO4/C

In this work, the La substitution of iron and replacing the oxygen with fluorine are both adopted to expectantly enhance the rate performance and structure stability of LiFePO4 during working. The characterizations of X-ray diffraction, scanning electron microscope, transmission electron microscope, charging-discharging tests, electrochemical impedance spectroscopy and safety tests are used to investigate the influences of La3+ and F− doping on the LiFePO4. The results indicate the cathodes after La3+ doping not only deliver the larger lattice parameters and unit cell volume to broaden the lithium ions migration pathway and accelerate the Li + diffusion speed, but also strengthen the whole bond energy of LiFePO4 owing to the high bond energy of La–O. In addition, the F replacement of O could increase the length of Li–O bonds and decrease the length of P–O bonds, further be helpful to enhance the Li + diffusion between LiFePO4 phase and FePO4 phase due to the weakening of Li–O bonds. Finally, the La3+ and F− co-doped cathode delivers the superior discharge capacity of 139.3 mAh g−1 at 5C high rate and 127.2 mAh g−1 at −20 °C, with the high discharging capacity of 160.1 mAh g−1 after 100 cycles at 45 °C.

Diffusion model of multi-agent collaborative behavior in public crisis governance network based on complex network evolutionary game

In order to explore the phenomenon of diffusion of group decision making formed by the emergence of decision-making behaviors of governance agents in public crisis governance systems, this research uses a complex network evolutionary game approach, considers BA scale-free networks as network vectors of public crisis governance systems, and develops a diffusion model of collaborative governance decision making behaviors. Simulation experiments are also conducted to show the macro-level impact of micro-subjects’ decision-making behavior on group “Emergence-Diffusion”. The results of this study show that the cost of collaborative governance has the most significant effect on the depth and breadth of the spread of collaborative behavior in governance networks. The size of the network determines the speed of network diffusion. The smaller the network size, the more sensitive it is to the spillover benefits of collaborative governance, and the larger the network size, the more sensitive it is to the penalties of non-compliance. The findings of the study have implications for the collaborative behavior of multiple agents in public crisis governance. The main findings are that (1) in order to ensure the stability of the collaborative governance system, decision making options should be selected according to the size of the network. (2) A reasonable penalty mechanism for breach of contract should be set up to avoid the phenomenon of “free-riding” in collaborative governance. (3) Reasonable allocation of collaboration benefits and maintenance of cooperative relationships between nodes in the neighborhood. (4) External regulators should ensure that information in the network is disseminated without barriers and reduce the phenomenon of information asymmetry.

Study on migration and diffusion law of MICP solution in fractured loess

In this paper, according to the migration and diffusion law of MICP solution in fracture-pore medium, the migration and diffusion equation of MICP solution in loess fracture-pore medium is derived at first. Then, the migration and diffusion test was carried out by using the self-made MICP solution migration and diffusion device. In the model, the aperture of the fracture of 0.5mm, 1.0mm and 1.5mm was selected, and the calcium ion concentration at different points was measured by atomic absorption method, so as to obtain the distribution map of calcium ion concentration. According to the test results, the migration speed of calcium ions in the direction along the fracture is less than the diffusion speed of the wet peak, and the vertical fracture direction is faster than the diffusion speed of the wet peak. The distribution range of calcium ion concentration increases first and then decreases with the increase of fracture opening. COMSOL software is used to compile the mathematical equation, and the whole process of MICP solution migration and diffusion is numerically simulated. The numerical calculation results are basically consistent with the experimental results, and the derived mathematical equation is reasonable.

Green technology diffusion model and simulation considering enterprise technology absorption capacity

ABSTRACT The diffusion and wide application of green technologies are important means to achieve climate change mitigation. Concerning the green technology absorption capacity and technology diffusion willingness of enterprises, this paper divided enterprises into four categories, constructed a green technology diffusion model and analysed the equilibrium point and stability of the model. Then, we studied the diffusion process and laws of green technology through simulation experiments. The results show that in the green technology diffusion system, the basic regeneration number is the key factor in determining the equilibrium state of green technology diffusion. The disease-free equilibrium point of the green technology diffusion system is globally asymptotically stable, and the endemic equilibrium point is locally asymptotically stable. In order to improve the speed and scale of green technology diffusion, it is necessary to create green technology diffusion sources through multiple channels, improve enterprise technology absorption capacity through multiple methods, and enhance enterprise green technology diffusion willingness at multiple levels.

Competitive adsorption of CH4/CO2 in shale nanopores during static and displacement process

During the development of shale gas, various issues such as low individual well production, rapid decline, limited reservoir control, and low recovery rates have arisen. Enhancing shale gas reservoir recovery rates has consistently been a focal point and challenge within the industry. Therefore, this paper employs molecular dynamic (MD) simulation methods to study the adsorption and diffusion characteristics of CH4/CO2 at different temperatures and mixing ratios. It compares the effects of temperature and CH4/CO2 molar ratio changes on the selectivity coefficient, adsorption capacity, and diffusion coefficient of CH4/CO2. The paper also plots the displacement interface and the function of CH4/CO2 injection/residual amounts over time. Furthermore, it analyzes the adsorption capacity of molecules on the graphene surface, the migration capacity of molecules in the slit, and the displacement process of CH4 by CO2 on the nanoscale, revealing the microscopic mechanism of CH4/CO2 competitive adsorption and displacement. The research results indicate that the influence of temperature on the selectivity coefficient is not significant, with an average decrease of 3% for every 20 K rise in temperature. Pressure has a more pronounced effect on the selectivity coefficient, with values around 1.4 at low pressures and around 1.2 at high pressures. Elevating the mole fraction of CO2 in the binary gas mixture results in an increase in the total adsorption amount and an accelerated variation of adsorption amount with pressure. As the CH4 mole fraction rises, the diffusion coefficient of CH4 increases, while the diffusion coefficient of CO2 diminishes with an increasing CO2 mole fraction. Under identical conditions, CO2 exhibits a stronger adsorption capacity over CH4 in shale organic nanopores, resulting in a concave moon-shaped displacement interface in the model. The larger the pre-adsorption pressure of CO2, the more intense the movement of CO2 along the graphene surface, and the faster the diffusion speed of CO2 along the wall. In a displacement pore (the pore space used to provide the displacement location or site) with a diameter of 3 nm, at smaller pressure differentials (≤10 MPa), the residual amount of CH4 remains relatively stable without substantial alteration. However, at a pressure differential of 20 MPa, the residual amount of CH4 decreases rapidly, and the displacement efficiency significantly improves.

Introduction dynamics: the advancement of peacock bass (Cichla sp.) in aquatic ecosystems of the pantanal (mato grosso)

The aim of this study was to survey the spatial distribution of the Cichla sp. species in aquatic bodies around the municipality of Cáceres-MT and the evolution of records for the Brazilian Pantanal. Collections took place in the marginal lakes and troughs of the Caramujo, Padre Ignácio and Paraguay rivers, with collections during high and low water periods in 2018 and 2019. Interviews were conducted with fishermen using a semi-structured questionnaire and obtaining locations where tucunaré occur. Secondary data was obtained by searching for articles on the occurrence of species in the Pantanal. Thirty-five specimens of Cichla kelberi were caught in 21 localities in the study area. Interviews revealed 44 localities, predominantly on the left banks of the Paraguay River. In the literature, there have been 9 studies on the occurrence of tucunaré in the Brazilian Pantanal, 7 of which in the southern Pantanal. The data points to a distribution of C. piquiti further south and C. kelberi further north in the biome, which may be due to the routes of introductions and the characteristics of the biome reducing the speed of diffusion.