In this study, immersion experiments were conducted on the geopolymer mortar (GPM) by using artificial seawater, and the effects of alkali equivalent (AE) and waterglass modulus (WGM) on the resistance of geopolymer mortar (GPM) to seawater immersion were analyzed. The test subjected 300 specimens to 270 days of artificial seawater immersion and periodic performance tests. Alkali equivalent (AE) (3–15%) and waterglass modulus (WGM) (1.0–1.8) were employed as influencing factors, and the mass loss and uniaxial compressive strength (UCS) were used as the performance evaluation indexes, combined with X-ray diffraction (XRD) and scanning electron microscopy (SEM) to analyze the time-varying pattern of geopolymer mortar (GPM) performance with seawater immersion. The findings demonstrated a general trend of initially growing and then declining in the uniaxial compression strength (UCS) of geopolymer mortar (GPM) under seawater immersion. The resistance of geopolymer mortar (GPM) to seawater immersion decreased with both higher or lower alkali equivalent (AE), and the ideal range of alkali equivalent (AE) was 9–12%. The diffusion layer of the bilayer structure of the waterglass particle became thinner with an increase in waterglass modulus (WGM), which ultimately led to the reduction in the resistance of the geopolymer structure to seawater immersion. Additionally, a support vector regression (SVR) model was developed based on the experimental data to predict the uniaxial compression strength (UCS) of GPM under seawater immersion. The model performed better and was able to achieve accurate prediction within 1–2 months, and provided an accurate approach to predicting the strength of geopolymer materials in a practical offshore construction project. It is known that concrete structural degradation and a considerable loss in service life are caused by seawater erosion in marine engineering. The more reliable explanation for why objects deteriorate is because seawater is high in corrosive ions such as Clronments . Insolub- concentrations in the activator caused cementitious building materials to lose strength. Dai et al. [Due to its excellent erosion resistance and mechanical properties, the geopolymer cementitious material has become a friendly substitute to solve the problem ,4,5. Owii et al.  investigi et al. . Recent i et al. ,13,14,15i et al.  effectivi et al.  investigi et al.  focused i et al.  investigFor geopolymer performance prediction, Behnood et al.  used theNumerous researchers have conducted some studies on the durability performance of geopolymer materials under seawater immersion and have demonstrated that geopolymer materials have excellent resistance to seawater immersion. However, these studies only focus on the relationship between the influencing factors and durability, and do not systematically analyze the time-varying patterns of geopolymer materials with seawater immersion. In addition, a large number of studies are only based on experimental results without subsequent performance prediction. Therefore, this study focused on analyzing the influence law of activator parameters and the time-varying law of performance under seawater immersion conditions, and establishing a prediction model for performance prediction by combining the experimental results.This study examined the effects of waterglass modulus (WGM) and alkali equivalent (AE) on the mechanical characteristics and durability of geopolymer mortar (GPM) under seawater immersion utilizing GPM specimens subjected to artificial seawater immersion for 270 days. AE  and WGM  were used as influencing factors, and mass loss and uniaxial compressive strength (UCS) were used as performance evaluation indexes, combined with X-ray diffraction (XRD) and scanning electron microscopy (SEM) to analyze the time-varying patterns and intrinsic causes of GPM performance with seawater immersion. To further realize the prediction of the strength of GPM under seawater immersion, a support vector regression (SVR) model was developed based on the experimental findings, which provides a basis and reference for the application of geopolymer materials in actual offshore construction projects.2 makes up 92% of the mass of SF, with an average particle size of 0.1 μm, and the specific properties of the materials are shown in 2O, 27.9% SiO2, and 63.5% H2O).Fly ash (FA), silica fume (SF), and slag were employed as three separate raw materials in this study to cast GPM. The slag is S95 ground granulated blast furnace slag in white powder form and the fly ash is low-calcium (CaO < 10%), and Ae and Mo were used as variables in GPM specimens to study the impact of AE and WGM on the performance of GPM under seawater immersion circumstances. The parameters are defined in Equations (1) and (2). Ae ranged from 3 to 15%, Mo ranged from 1.0 to 1.8, and the mass ratio of sand aggregate to base material was 2.0. The specimens were split into two groups of A and M for preparation. Ae is the mass ratio of the equivalent basic oxide (Na2O) in the activator (Na2SiO3) to the activated solid powder, and it is computed as follows:Mo is the molar ratio of equivalent SiO2 to equivalent basic oxide (Na2O) in the activator (Na2SiO3), and it is computed as follows:The alkaline activator was prepared by sodium hydroxide flakes and sodium silicate solution 24 h in advance. To lessen the impact of unknown impurities, sodium hydroxide flakes were dissolved in distilled water, mixed proportionately with sodium silicate solution, and kept at room temperature  for storage. The base material and sand aggregate were mixed in the mixer for 20 min and cooled to room temperature. Then, the prepared alkali activator was added and stirred into shape. A normal mortar cube of 70.7 mm in height, width, and depth was used as the specimen, with 30 specimens in each group. The surface of the specimen was covered with plastic film after it was manufactured to stop moisture loss and cracking. The samples were exposed to a standard curing chamber temperature of 23 °C ± 2 °C for 24 h before being demolded and tagged. The specimen was kept in the maintenance room with film and water after it was demolded until the 28 days test age.The maintained GPM specimens were immersed in artificial seawater. The artificial seawater liquid level was at least 50 mm above the specimen and the specimen interval was not less than 50 mm. Plastic film was used to seal the immersion chamber and the artificial seawater was replaced every 30 days. The mass change test was conducted for fixed specimens throughout the seawater immersion phase in order to diminish the impact of individual specimen variances on the test findings. The samples were periodically removed from the immersion chamber and put into a drying chamber at a constant temperature of 105 °C for drying until the quality no longer changed. The samples were weighed using an electronic scale with an accuracy of 0.01 g. A WES-600 universal testing machine was used to determine the UCS of the samples. The fine morphological characterization of GPM was performed by SEM using JEOL’s JSM-IT500 , and the reaction products and compositions were analyzed by XRD. The artificial seawater was prepared with reference to the standard ASTM D 1141-98 (2013), and the main salt contents of the artificial seawater are shown in + and Mg2+ while the anions are primarily Cl− and SO42−. Artificial seawater was prepared and replaced monthly to weaken the effect of water evaporation on seawater concentration.The configuration of artificial seawater with ion concentration was increased to three times in order to speed up immersion and reduce the test period. The main dissolved ions and their mass percentages are presented in It is evident that while the geopolymer material has good resistance to seawater immersion, structural degradation with increasing seawater immersion time is unavoidable. In actual offshore construction projects, if the strength of the geopolymer structure can be predicted in advance, engineering disasters caused by structural deterioration can be effectively avoided. In order to give an effective and scientific technique for the precise prediction of GPM strength under seawater immersion, this research regressed and predicted the time-varying UCS of GPM under seawater immersion based on the support vector regression (SVR) model.MSE and the coefficient of determination R2 of the test set were recorded and calculated as:l is the number of samples in the test set; iy  is the true value of the ith sample; i = 1, 2, …, l) is the predicted value of the ith sample.Support vector machine (SVM) is a better algorithm for solving small-sample, nonlinear, and high-dimensional problems based on the statistical Vapnik–Chervonenkis (VC) dimensional theory and the principle of structural risk minimization . SVR is MSE and R2, the established regression models were assessed. Changing the kernel function and other model parameters until the performance satisfies the requirements was performed to the model if the performance did not satisfy the requirements.According to ix, iy), i = 1, 2, …, 50}, where ix is the influence factor of the ith sample, and iy is the UCS corresponding to the ith sample. The measured data (No. 1–45) before 270 days of immersion were used as the training set, and the measured data (No. 46–50) at 270 days of immersion were used as the test set to construct the SVR prediction model. The sample data are shown in The SVR prediction model only considers the effects of three factors, AE, WGM, and seawater immersion time. In order to better evaluate their effects on the compressive strength of GPM, the data of A and M groups were processed independently. Let the sample be {accuracy ,25. Cons4− in the geopolymer mesh structure has negative charge and needs cations such as Na+ and Mg2+ to balance the charge [+ and Mg2+ in the seawater prior to immersion diffuse into the interior of the geopolymer, resulting in an increase in mass. Notably, sea salt crystals were discovered during the SEM investigation  during the test causes the solution to quickly crystallize, preventing it from effectively participating in the polycondensation reaction to generate strength.The initial uniaxial compressive strength of GPM was measured when they were not eroded by seawater, and the results are shown in tructure . It is w2+ and K+ in seawater that enter the reticular structure of GPM and replace the Na+ equilibrium charge to stabilize the silica-aluminate reticulation are to blame for the strength enhancement in the initial stage. This is consistent with the increment in the mass of GPM specimens in the pre-seawater immersion period. Contrarily, the UCS of GPM decreased at a later stage with increasing immersion time, which was attributed to a decrease in calcium content [ content . Chi and content  attribut2)m as the cores, the outer layer of the cores adsorbs a large amount of negatively valent H3SiO4−, the negatively valent H3SiO4− and part of the Na+ are distributed within the dense layer, and another part of Na+ is free in the diffusion layer, which finally forms the bilayer. An increase in the modulus generates more negatively valent H3SiO4−, and more Na+ is adsorbed within the dense layer leading to a forced thinning of the diffusion layer and a decrease in the free Na+ and OH- content. As per the “depolymerization-condensation” theory of Davidovits [4+, Al3+, and Ca2+, which are involved in the formation of structure in raw materials, need to be activated by Na+ and OH-. Consequently, the high modulus leads to the reduction in Si4+, Al3+, and Ca2+ in the system, which cannot form a more dense and complete condensation structure, so the resistance to seawater immersion is poor. On the other hand, it is likely that the increment in WGM resulted in a decline in the relative amount of Na2O and a reduction in the impact of alkali activation, which led to a loss of strength [2O was the same.The change pattern of the UCS of GPM specimens with seawater immersion time and WGM is shown in vidovits , the Si4strength . It was An XRD diffraction study on GPM specimens with various AE, WGM, and immersion times was carried out in order to further investigate the internal process of the change in geopolymer material properties; the findings are shown in + helps to produce zeolite phase crystallization while OH- in NaOH speeds up the dissolution of Si4+ and Al3+ in the raw material. Due to the low NaOH content in the low-AE environment, neither the OH- nor the Na+ levels were sufficient to fully dissolve the Si4+ and Al3+ in the raw material, which prevents the network from fully polymerizing [2 with swelling properties, which weakens the bond between the geopolymer gel and the aggregate. The SEM picture of GPM following 270 days of seawater immersion is shown in GPM specimens with various AE, WGM, and immersion times were chosen for SEM to explore the microstructure in order to further analyze the change in geopolymer material properties and the internal process of seawater immersion, and the findings are displayed in merizing ,39. All Utilizing the developed SVR model, the regression prediction of GPM strength under seawater immersion was carried out. MSE and R2 results for the training and test sets are presented in MSE, reaching 10−3, and R2 was above 0.97; the MSE of sample M also reached 10−3, and the R2 was more than 0.99. It is clear that the prediction results of both sample sets were in good agreement with measured results, and the SVR model was able to predict the time-varying UCS of GPM under seawater immersion with a good accuracy. By comparing the MSE and R2 of the two groups, it is obvious that the training effect for sample A was weak and the R2 of the training set was quite low, which was caused by the discrete character of the data. In contrast to WGM, the influence of AE variations on GPM strength had a wider range. The extreme difference of sample A was 39.42 MPa, whereas the extreme difference of sample M was 26.35 MPa. The dispersion of Sample A was larger than that of M; hence, the training impact of the regression model was generally subpar.The C and kernel function variance g of the model were obtained with the help of the cross-validation method. The results are illustrated in In this study, the RBF was used to train the SVR, and the optimal parameter penalty factor C represents the weight given to outlier samples, and the higher the value of C, the more samples must be used as a support vector for the model. The penalty factor C of sample A in this study was significantly larger than that of sample M, indicating that sample A required more support vectors for training. The influence distance of a single training sample was managed by the kernel function variance g. The radius of effect was narrower with a greater value of g, and the sample values must be highly similar to one another before they can be categorized as belonging to the same sort, which leads to the overfitting phenomena. Sample A’s g was modest, suggesting that the model support vector had a larger radius of sample effect during training. This phenomenon was still caused by the discrete nature of the data.The penalty factor The same data were subjected to regression analysis using a neural network prediction model in order to compare and evaluate the applicability of the SVR model. R2 of the BP neural network’s prediction results was calculated as 0.99 and 0.91, respectively. The R2 and goodness-of-fit of the BP neural network model decreased as compared to the SVR model  in comparison to 270 days, and the projected values of compressive strength were higher than the true values . This isIn summary, the SVR model outperforms the artificial neural network model for predicting the strength of GPM under seawater immersion, and in the case of small samples and short-term prediction, the SVR model can more accurately predict the trend of the strength of geopolymer structures under seawater immersion, particularly the relationship with AE and WGM. Additionally, the created SVR model can forecast the compressive strength of GPM with high accuracy in 1–2 months, which can offer a reliable, scientific way for predicting the strength of geopolymer materials in actual offshore construction projects.The effects of AE and WGM on the performance of GPM before and after seawater immersion were investigated, as well as the effective prediction of GPM strength under seawater immersion using the SVR prediction model. The following conclusions can be reached after discussing the results of the above sections:(1) The time-varying law of UCS of GPM with seawater immersion was obtained. The UCS of GPM showed a trend of rapid increase followed by slow decrease. The rapid increment in strength from 0 to 60 days was related to the charge balancing of metal cations in seawater entering the reticular structure of the GPM; the gradual decline in strength after 60 days was attributed to the reduction in the gel phase structure.(2) The influence of AE and WGM on the resistance of GPM to seawater immersion was studied. The GPM became less resistant to seawater immersion as AE increased because it produced more free alkali. The GPM construction revealed that the best resistance to seawater immersion when AE was in the range of 9%-12%. The diffusion layer of the bilayer structure inside the waterglass micelle attenuated as WGM increased (>1.0), and the resistance of GPM to seawater immersion decreased as a result.(3) The mechanism of seawater immersion was exposed. The XRD and SEM data indicated that the hydrolysis of the gel phase in the geopolymer structure was primarily responsible for the immersion of seawater and did not produce a significant amount of new destructive material.(4) Time-varying intensity regression and prediction of GPM were achieved. The SVR prediction model could more accurately estimate the trend of the UCS of GPM during seawater immersion, especially in respect of AE and WGM, with limited samples and short-term forecast. It could accurately forecast the UCS of GPM within 1–2 months, which can offer a reliable, scientific way to predict the strength of geopolymer materials in real offshore construction projects.This work investigated the effects of AE and WGM on GPM performance before and after seawater immersion, and used the SVR model for the first time in predicting GPM strength under seawater immersion. However, the study still has some limitations, such as more complex influencing factors. Multi-influencing factors such as activator type and aggregate type can be introduced in future studies. Studying more influencing factors requires further improvement of the algorithm, so swarm intelligence algorithms such as the dragonfly algorithm (DA) and whale optimization algorithm (WOA) can be used in future studies ,41,42,43


African swine fever (ASF) is a severe infectious disease affecting domestic and wild suids. Spatiotemporal dynamics analysis of the ASF is crucial to understanding its transmission. The ASF broke out in Vietnam in February 2019. The research on the spatiotemporal evolution characteristics of ASF in Vietnam is lacking. Spatiotemporal statistical methods, including direction analysis, spatial autocorrelation analysis, and spatiotemporal scan statistics were used to reveal the dynamics of the spatial diffusion direction and spatiotemporal aggregation characteristics of ASF in Vietnam. According to the cessation of the epidemic, it was divided into three phases: February to August 2019 (phase 1), April to December 2020 (phase 2), and January 2021 to March 2022 (phase 3). The ASF showed a significant spread trend from north to south in phase 1. The occurrence rate of the ASF aggregated spatially in phase 1 and became random in phases 2 and 3. The high−high ASF clusters (the province was a high cluster and both it and its neighbors had a high ASF occurrence rate) were concentrated in the north in phases 1 and 2. Four spatiotemporal high-risk ASF clusters were identified with a mean radius of 121.88 km. In general, there were significant concentrated outbreak areas and directional spread in the early stage and small-scale, high-frequency, and randomly scattered outbreaks in the later stage. The findings could contribute to a deeper understanding of the spatiotemporal spread of the ASF in Vietnam. Ornithodoros moubata) and the fly  can transmit the ASFV [African swine fever (ASF) is a severe infectious disease caused by the African swine fever virus (ASFV) and it dominantly affects domestic and wild suids ,2. The Athe ASFV ,13. The the ASFV . The ASFthe ASFV ,15,16.The ASF originally emerged in East Africa in the early 1900s and has traditionally been present in the African continent ,16,17; tVietnam is the first country in Southeast Asia to report the ASF. In February 2019, the first ASF outbreak was officially reported in the Hung Yen province in Northern Vietnam and then spread to the entire country within 5 months . There wGene sequencing can provide clues for tracing the origin of the epidemic; for example, studies showed that the ASFV isolates of the first outbreak in Vietnam belonged to the ASFV strains sequenced in Georgia and China ,23. HoweThis study aimed to increase knowledge of the temporal and spatial evolution of the ASF in Vietnam, including its spreading direction and spatiotemporal clustering characteristics. The ASF epidemic data in Vietnam from 1 February 2019 to 31 March 2022 were collected from the EMPRES-i Global Animal Disease Information System of the Food and Agriculture Organization of the United Nations (FAO) . The infiR refers to the proportion of communes (town districts or wards) with ASF in the ith province  per month in a given period, iA refers to the number of reported ASF outbreaks in the ith province in a period, iC refers to the number of communes of the ith province, and t is the number of months in the period. The numbers of communes in each province in 2019 and 2020 were obtained from the Statistical Yearbook of Viet Nam [The average ASF occurrence rate in each province  per month was calculated using the following formula:Viet Nam ,37.I and Anselin Local Moran’s I, were used to reveal the clustering characteristics of different epidemic stages at the provincial level respectively; the spatiotemporal scanning statistics aimed to reveal the spatiotemporal high clusters at the daily outbreaks scale.Based on the perspective and spatiotemporal scale of the spatiotemporal characteristics of the ASF epidemic in Vietnam to be revealed, we selected three spatial analysis methods . In partInaccurate outbreak timing may affect the accuracy of the direction analysis, for which it was decided to reveal possible directions on a monthly scale. Firstly, the monthly overall outbreak centers of the ASF were detected using the central feature analysis performed in the ArcGIS software  . Then thiD refers to the distance accumulation of the ith ASF outbreak and ijd refers to the distance between the ith outbreak and the jth outbreak. The central feature analysis requires three or more outbreaks. When there were less than three ASF outbreaks in a month, the first outbreak was taken as the outbreak center.The outbreak center was identified with the smallest distance accumulation from all other ASF outbreaks in a month. The distance accumulation was calculated by the Euclidean method and the formula was as follows:p < 0.05).In the direction test, an infection chain was constructed based on the chronological order of the monthly ASF outbreak centers. Directed line segments were used to connect the outbreaks. The average angle and the angular concentration were calculated during the direction test. Angles are taken as rotated counterclockwise degrees from the horizontal, with East corresponding to 0 and North to 90. Concentration is in the range of 0 to 1, with 1 indicating an angular variance of 0. A consistent direction of the spread of cases will result in an angular concentration near 1. A random spread of cases will result in an angular concentration near 0. The time connection matrix was set as relative . The significance of the test statistic was estimated by the Monte Carlo simulation . When the z-score or p-value indicates statistical significance, a positive Moran’s I index value indicates a tendency toward clustering while a negative Moran’s I index value indicates a tendency toward dispersion.Global Moran’s iI > 0 indicates that the ith province is part of a cluster, surrounded by provinces with similarly high or low values. Local Moran’s iI < 0 indicates that the ith province is an outlier surrounded by provinces with dissimilar values. Based on iI, z-score and p-value, the provinces can be classified into five types: (1) High-high (HH) indicates a statistically significant cluster of high values; (2) Low-low (LL) indicates a statistically significant cluster of low values; (3) High-low (HL) indicates an outlier in which a high value is surrounded primarily by low values; (4) Low-high (LH) indicates outlier in which a low value is surrounded primarily by high values; (5) ‘not significant’ indicates no spatial autocorrelation.Local Moran’s I analysis revealing the spatial clusters or outliers of the epidemic within three phases, the retrospective spatiotemporal scan analysis detected ASF high-risk clusters in a continuous time range throughout the study period on a daily scale. The retrospective spatiotemporal scan analysis was performed using SaTScan software  [Compared with the Local Moran’s MA, USA) . Based oMA, USA) ,45. It iMA, USA) .p-value). The relative risk (RR) was the ratio of the number of observed ASF outbreaks in a cluster to the expected one, indicating the infection risk in a cluster compared to that in other areas [The parameters necessary to run the model include the unique code, geographic location (longitude and latitude), and date of the ASF outbreaks. The analysis used a circular window to search the high-risk clusters. The scanning window moved in time and space to cover every possible geographic location and time interval. To ensure accuracy, days were used as the time unit to reflect the spread of the ASF. The maximum spatial cluster size was defined as 50% of the total number of ASF outbreaks and the maximum temporal cluster size was defined as 90 days . The higer areas ,32.A total of 665 ASF outbreaks were reported in Vietnam from 1 February 2019 to 31 March 2022 . It can p < 0.01)  . The ave < 0.01) a, the sp < 0.01) b,c, the I = 0.47, z-score = 8.14, p < 0.01) (p > 0.05).The ASF occurrence rate in phase 1 had a significantly positive spatial correlation, indicating that the spatial distribution pattern was aggregated at the provincial level ( < 0.01) . The spaSix provinces or municipalities were identified as HH clusters in phase 1: Bac Ninh, Ha Nam, Ha Noi, Hai Phong, Hung Yen, and Thai Binh a. Three p < 0.01) and were sorted by LLR from high to low. With a radius of 46.76 km and a risk of outbreak 5.47 times higher than in other areas (p < 0.01), cluster 1 covered 79 outbreaks in five provinces  from 1 February to 8 March 2019 in phase 1 and concentrated in the Thai Binh province with 45 outbreaks. Cluster 2 covered 31 outbreaks in the Tuyen Quang, Yen Bai, and Bac Kan provinces from 16 September to 11 November 2019 in phase 2. Cluster 3 had the highest RR of 6.65 and the shortest duration of 12 days from 12–23 February 2022 in phase 3 and covered 26 outbreaks in five provinces . Cluster 4 had the largest radius of 254.01 km and the longest duration of 76 days from 25 January to 12 April 2021 in phase 3, covering 26 outbreaks in four provinces . Space−time scan analysis identified four spatiotemporal high-risk clusters, with a total of 165 outbreaks, a mean radius of 121.88 km, and a mean duration of 45.5 days , Table 4The number of ASF outbreaks in March 2019 was much higher than in other months of 2020–2022. All outbreaks (100%) occurred at backyard pig farms with no or low biosecurity at the beginning . Since tThe ASF was stopped seven months after the first outbreak. Necessary measures were implemented to control and stop the spreading of the ASF in Vietnam after the first detection: early detection, culling, disinfection, and compensation; strictly movement control of pig and pig products; biosecurity application in big farms; risk communication and public awareness; and information sharing and international collaboration ,46.The ASF reappeared in April 2020. The Vietnamese government endorsed the “National Plan for the Prevention and Control of African Swine Fever for the period of 2020–2025” on 7 July 2020, which set goals for ASF control, pig farm biosecurity application, and laboratory capacity development to be achieved; defined restocking conditions, sampling requirements, surveillance, conditions for culling, and moving-to-slaughter .The ASF outbreak has swept across 63 provinces across the country in phase 1. After a nationwide outbreak, the number of provinces that have reported the ASF in phases 2 and 3 was 29 and 41, respectively . The aveThe new ASF outbreaks decreased significantly in March 2022 compared to February. This may be related to the implementation of the Month of Environmental Sanitation and Disinfection aimed at actively preventing disease outbreaks in domestic animals in high-risk areas that started on 15 March 2022 . The preThere were seasonal differences in outbreaks of the ASF epidemics in Vietnam. From February to March in 2019, 2021, and 2022, the number of ASF outbreaks increased significantly . The incIn both phases 1 and 2, the ASF broke out first in the north, and the HH clusters and the high-risk cluster areas were both located in the north. The virus most likely entered the country from abroad through the illegal movement of pigs and pork products or food with the ASFV brought by international travelers to Vietnam ,46,52. TThe overall ASF outbreak center changed from north to south in phase 1 . This trIn phase 1 (February 2019–August 2019), there was a high-risk cluster from 1 February to 8 March 2019 , which rhttps://wahis-uat.oie.int, accessed on 17 May 2022) and the FAO’s EMPRES-i . The differences between the two datasets are mainly reflected in the sources of data collection , reporting methods , reporting content  [The limitation of this study is the uncertainty of the data. Typical animal disease outbreak information is usually obtained from the datasets published by two international agencies: the OIE’s WAHIS (cidence) ,54,55. Ccidence) . Comparicidence)  and masscidence) ,22, the The integrated use of multiple spatiotemporal analysis methods has been proven to be able to comprehensively reveal the spatiotemporal distribution characteristics of the epidemic from multiple perspectives studied in Vietnam. In general, there were significant concentrated outbreak areas and directional spread in the early stage of the introduction of the ASF virus into Vietnam and small-scale, high-frequency, and randomly scattered outbreaks in the later stage; this could contribute to a deeper understanding of the spatiotemporal spread of the ASF in Vietnam.


In this paper, the strength characteristics and erosion resistance of solid waste incineration (MSWI) powder were studied. Firstly, the optimum process for the preparation of regenerated powder from MSWI bottom slag by ball milling was determined as follows: rotational speed 350 r/min, time 45 min. The strength activity index of regenerated powder reached the maximum when the substitute content of powder was 30%. Secondly, the semi-erosion method was used to study the strength variation rule of mortar with different content of MSWI powder in semi-immersion of salt solution. It was found that the higher the content of MSWI powder, the greater the anti-erosion coefficient of mortar specimen. Finally, the capillary rise test, crystallization test and capillary pore water absorption test were used to study the total porosity, coarse capillary-pore porosity and fine-capillary pore porosity of concrete containing MSWI powder. The results showed that, with the increase in MSWI powder content, the above pore structure properties were improved. The results revealed the transport and crystallization process of salt solution in concrete mixed with MSWI powder and the mechanism of corrosion resistance. With the continuous development of construction engineering, concrete structure is widely used in construction, bridge, road and other structural engineering. The durability mechanism of concrete structure has become the focus of global attention, which is the most critical index affecting construction quality. In practical engineering, the durability of concrete materials is mostly damaged by sulfate and chloride, which is also the most complicated and destructive cause of concrete structure damage ,2,3,4,5.2SO4-Thenardite, Na2SO4·10H2O-Mirabilite, and Na2SO4·7H2O-Sodium sulfite heptahydrate. Among them, Na2SO4·10H2O was difficult to maintain at a stable state and was easily decomposed into Na2SO4 and Na2SO4·7H2O. The changes of temperature and humidity also had a significant influence on the chemical composition of sodium sulfate crystals. The sulfate resistance of concrete was affected by its shape and appearance, permeability resistance and compactness [Sodium sulfate was the most widely distributed sulfate solution in nature and had the most serious erosion to concrete ,7. Accorpactness ,18,19,20pactness ,22,23,24pactness ,26,27,282 so as to improve the structure of concrete transition zone and enhance the sulfate erosion resistance of concrete. Fly ash can also increase the resistance of HPC to sulfate corrosion [2 generated in the secondary hydration reaction of concrete; thus, the sulfate resistance of concrete can be improved. However, as a new type of admixture, there is little research on urban-life incinerations for bottom slag with respect to the durability of concrete.In view of the study on the durability of concrete by mineral admixtures, Qin Lixiang believed that using more fly ash instead of cement can reduce the pore structure of cement concrete and the content of Ca(OH)orrosion . When thorrosion , but theorrosion . The addorrosion , and the42−/Cl− solution erosion performance of mortar samples containing MSWI was studied to discuss the variation of anti-corrosion coefficient with the amount of fine powder. The crystallization transport process of salt solution in bottom slag recycled concrete was also studied. By studying the change of porosity of recycled concrete containing MSWI bottom slag and the correlation between capillary pore gaps and different factors, the mechanism of the salt crystallization resistance of recycled concrete containing MSWI bottom slag was revealed.In this paper, the anti-SOThe MSWI residue used in this experiment was obtained from a waste incineration power plant in Huai’an city, Jiangsu Province. The samples randomly selected on site were generally gray and black, and after drying, they were gray and white with a slight odor, as shown in The ordinary Portland cement of strength grade 42.5 was used, which was in line with the general Portland cement (GB175-2009) standard provisions. The adoption of standard sand was in line with China’s new standard ISO. The industrial grade anhydrous sodium sulfate and anhydrous sodium chloride were >99.0% and 99.5%, respectively. The recycled concrete containing MSWI was tested using natural sand and gravel in accordance with JCJ 52-2006 standards, and polycarboxylic acid high-efficiency water-reducing agent was used as the water-reducing agent.In this experiment, the influence of ball mill rotation speeds and ball grinding time on MSWI residue regeneration was considered. Firstly, the grinding time was 30 min, and the bottom slag was ground at the rotation speed of 200 r/min, 250 r/min, 300 r/min, 350 r/min, 400 r/min, and 450 r/min to obtain the fine powder. The residue ratio was measured by a 80-mesh sieve, and the specific surface area of MSWI residue was measured by a laser particle size analyzer to find out the optimal speed of the ball mill under fixed grinding time. Under the optimum speed of ball mill, the influence of time factors on the regeneration efficiency of MSWI bottom slag was determined. The bottom slag was ground for 15 min, 30 min, 45 min and 60 min at the optimal speed, and the screening residual rate of micro-powder was determined using a 80-mesh sieve. The specific surface area of micro-powders was determined by a laser particle-size analyzer, and the optimal ball milling time was determined.The Dkz-6000 electric bending test machine and automatic constant pressure compression test machine are used for mortar strength tests. According to the method required in GB17671-1999 , the morThe erosion and damage of sodium sulfate crystals on mortar specimens containing MSWI were investigated in the laboratory. Sodium sulfate solution mainly entered cement-based materials through capillary action. In this experiment, the method of semi-immersion experiment was adopted, and the mortar specimen was formed by a triple mold of 40 mm × 40 mm × 160 mm. After standard curing for 28 days, the specimens were divided into two groups, which were first heated and dried in the oven. The first group was half-soaked in clean water, and the second group was half-soaked in 5% sodium sulfate solution see . The efftw is the mass change rate of the specimen when the age of erosion is t; tm is the mass of the specimen when the erosion age is t, unit/kg; m0 is the initial mass of the specimen, unit/kg.After the mortar specimen containing MSWI was corroded by sodium sulfate solution, the specimen expanded and its surface spalled, resulting in mass loss. The water on the surface of the specimen dried and then the water was poured on an electronic scale for quality measurements. The accuracy of electronic scale needed to reach 0.01 so as to accurately calculate the rate of mass change. The mass change rate of specimens is calculated by Formula (1):The influence of physical erosion of mortar specimen containing MSWI by sodium sulfate crystallization can be evaluated by calculating the corrosion resistance coefficient. The compressive and corrosion resistance coefficient referred to the ratio of the compressive strength of specimens with the same curing age and the same mixing ratio soaked in salt solution and water. The flexural and corrosion resistance coefficients referred to the ratio of flexural strength of specimens with the same curing age and the same mix soaked in salt solution and clean water, as described in Formulas (2) and (3).miK is the compressive corrosion resistance coefficient of the specimen at the i th erosion age; miR1 is the compressive strength of the specimen at the i th erosion age in salt solution, unit/MPa; miR2 is the ith erosion age of the specimen in clear water compressive strength, unit/MPa; niK is the flexural and corrosion resistance coefficient of the specimen at the i th erosion age; niR1 is the flexural and corrosion-resistant coefficient of the specimen in the salt solution at the i th erosion age, unit/MPa; niR2 is the compressive strength of the specimen at the i th erosion age in clean water, unit/MPa.C0 was taken from the mixture of sodium chloride and saturated Ca(OH)2. Cement-based materials and sodium chloride solution were sealed in a beaker and then placed in a curing chamber for one week.For chloride ion erosion tests of mortar containing MSWI, S1–S4 samples with different dosage of MSWI were prepared according to C1 (mol/L) was measured. Then, continue to add 50 mL (V4) of distilled water and a small amount of Ca(OH)2 solution into the beaker to make the solution a saturated Ca(OH)2 solution. The beaker was sealed in the curing chamber for three days, and the equilibrium solution was taken out from the beaker. The concentration of chloride ions in the equilibrium solution was C2 (mol/L), and the formula is shown in (4):C01 is the concentration of AgNO3, unit mol/L; V1 is the capacity of AgNO3 consumed by the first titration, unit mL; V2 is the capacity of AgNO3 consumed by the second titration, unit mL.After a week, the transparent liquid was removed from the beaker and its chloride ion concentration V0 volume is 100 mL; C0 is the concentration of NaCl solution saturated with Ca(OH)2; W1 is the binding amount of all chloride ions , in unit 10−3; gM is the total amount of gel material (cement and micro-powder), unit g; m is dry sample mass, unit g; m0 is the water requirement of cementing material (cement and powder) per unit mass, and the value is 0.25; W1 is the dimensionless ratio of cementitious material to the total amount of cementitious material and sand; α is the degree of hydration, α = M1/m0; W2 is the chemical binding amount of chlorine ion per unit mass of gel (cement and micro-powder), unit 10−3. W3 is the physical adsorption amount of chloride ion per unit mass of gel (cement and micro-powder), unit 10−3; V3 is the first equilibrium solution used for titration, unit mL.The calculation formulas for the binding amount of chloride ions are shown in (5), (6), (7) and (8):All concrete specimens used in this experiment were tested in accordance with the standard JGJ 55-2000 , and them1 measured by an electronic balance. Then, it was placed in the curing chamber at 90% relative humidity for 30 days. When water diffusions in concrete reache equilibrium state, the mass m2 of the same specimen was measured again. Under the condition of T = 105 °C, the specimen was dried to a constant weight and finally weighed m3 after cooling to calculate concrete porosity. The specific equations are shown in (9), (10) and (11):P1 is the coarse capillary porosity; P2 is the total porosity; P3 is the fine capillary porosity; M1 is the mass of saturated, unit kg; M2 is the mass of concrete specimen placed at 90% relative humidity for 30 d, unit kg; M3 is the mass of dry concrete specimen, unit kg; ρ1 is the density of concrete specimen, unit kg/m3; wρ is the density of water in kg/m3.The porosity of concrete can be obtained indirectly from the water loss rate of saturated concrete specimen. Concrete samples were made of 100 mm × 100 mm × 100 mm by the vibration molding method. After curing for 28 d and vacuum saturation, the water on the surface of the concrete samples was wiped with a dry cloth first. The mass of the samples was VS = L/T of osmotic crystallization rate is calculated, and the unit is cm/s. The experiment was carried out at room temperature, and the experimental device is shown in For the capillary rise experiment and capillary crystallization experiment of reclaimed concrete containing MSWI, 150 mm of side length concrete was first made according to the mix ratio. After 28 d curing in the curing room, a cylinder with a diameter of 100 mm and height of 150 mm was drilled on the concrete specimen with the core machine, and moisture was dried in the oven. The core body was half immersed in sodium sulfate solution, and the rising height of the surface of the core body of different specimens was measured. The remaining holes of concrete after core removal were closed. In the use of 5% sulfuric acid solution drops into the hole, crystallization from the surface of the concrete test block penetration time T and the concrete side wall thickness L were tested. Through the relation between the time T of crystallization penetrating out from the surface of concrete test block and the inner wall thickness L of concrete, the formula W at 10 time points in 24 h. The experimental device is shown in For capillary water absorption tests of reclaimed MSWI concrete, a concrete cube with a side length of 100 mm should be made. After curing for 28 d, it should be sealed with oxidized grease around it and placed into a drying box for drying. The test block was semi-immersed in a solution of sodium sulfate with a water surface height of 5 cm. It was taken out every once in a while and dried with a wet cloth. The weight of the test piece was immediately weighed. The experimental measurement time was the accumulated water absorption ΔAt a fixed time of 30 min and 45 min, the cumulative pass rate of 80 mesh corresponding to different speeds is shown in The specific surface area of MSWI powder at different rotational speeds is shown in 2/g, which obviously exceeded the specific surface area specification of conventional cement. The continuous increase in speed accelerates the wear of the machine and the consumption of electric energy; thus, 350 r/min was selected as the optimal speed.Based on the above experimental results and analysis, when the rotational speed was 350 r/min, the residue ratio of 80 mesh regenerated powder had reached a high level, and the specific surface area of the regenerated powder reached 7000–8000 cmThe compressive test results and strength activity indexes of different powder dosages are shown in The test results of 28 d flexural strength of mortar containing MSWI with different dosage are shown in The content of calcium oxide in MSWI powder was lower than that of cement, and there were few effective hydration products that can promote strength growth in the early stage. Therefore, the strength of mortar specimens containing MSWI was lower than that of pure mortar. On the other hand, MSWI powder was rich in silicon oxide and alumina, which can promote the pozzolanic reaction and effectively increase the later strength of cement-based materials. When the amount of MSWI powder was small, aluminum acid ions, sulfate ions and some unhydrated calcium oxide in cement-based materials were hydrated and regenerated into crystals, thus increasing the strength of mortar. However, the mass substitution of MSWI powder significantly reduced the content of calcium oxide in the paste, resulting in a reduction in crystals formed by aluminate ions as sulfate ions.2 in the mortar specimen dissolves, SO42− radical ions in the external solution also enter the interior of the specimen to carry out chemical reactions, thereby increasing the mass of the MSWI-containing mortar specimen [1 specimen was 12% higher than that of the S2 specimen when eroded for 180 d. The mass increase in the S1 specimen was 20% higher than that of the S3 specimen, and the mass increase in the S1 specimen was 27% higher than that of the S4 specimen.specimen . It can 42− ion erosion, SO42− ions entered the mortar structure and participated in the reaction, forming sodium sulfate crystals with filling and compacting effect, and the strength of the specimen increased at this time. However, as the erosion age further increased, the accumulation of sodium sulfate crystals caused the specimen to expand and form micro-cracks, which reduced the strength of the specimen. From the beginning of erosion to the age of 180 d, the compressive corrosion resistance coefficients of the four groups of specimens were S1 < S2 < S3 < S4, and the compressive corrosion resistance coefficients of S1, S2, S3 and S4 at 180 d were 0.92, 0.97, 0.98 and 1.02, respectively, indicating that MSWI powder as an active admixture can resist sulfate erosion in mortar.− ions did not erode the internal structure of green mortar significantly under semi-immersion conditions. No damage such as spalling and cracking was found on the surface of the MSWI-containing mortar specimens with different contents [contents .The research showed that the cement hydration products—calcium silicate hydrate (C-S-H) gel—not only had chemical adsorption to chloride ions but also have physical adsorption to chloride ions, and physical adsorption contributes greatly to the total adsorption amount . Since 2 in cement-based materials to form hydrated aluminate phase and other derivatives. The aluminate hydrate reacts with chloride ions to form Friede salts, so the cement-based material had a strong chemical combination with chloride ions. Due to the high specific surface area (7000–8000 cm2/g) of MSWI powder particles, more chloride ions can be adsorbed on the surface of MSWI particles so that the physical adsorption capacity of MSWI-containing mortar increases.The compressive strength test results of concrete specimens containing MSWI are shown in The pore structure and porosity were key factors affecting the strength of cement-based materials, which were also decisive factors for the resistance of cement-based materials to salt solutions. When the porosity was large and the pores were interconnected, the corrosion resistance of cement-based materials was poor. On the contrary, when the porosity was smaller, the concrete was more compact, and the erosion resistance of concrete can be better obtained. Therefore, the concrete containing MSWI had better corrosion resistance.With the increase in MSWI powder content, the compressive strength and flexural strength of mortar specimens at various ages showed a decreasing trend, and the reduction in flexural strength was larger than that of compressive strength. The micro-powder had little influence on the strength of recycled mortar in the early stage, but it had significant influences on the strength in the later stage. The strength activity index of regenerated powder was about 55% when the content of regenerated powder was 30%.With the passage of the sample’s half-soaking time in sodium sulfate solutions, the mass loss rate of mortar decreased gradually with the increase in MSWI content, while the corrosion resistance coefficient increased first and then decreased. Under the condition of constant w/c ratio, the salt crystal erosion resistance of mortar can be improved effectively with the addition of MSWI powder.The cement-based materials containing MSWI had a high ability to bind chloride ions. With the aging of curing, the performance of cement-based materials to bind chloride ions decreased. The total porosity, coarse capillary porosity and fine capillary porosity of recycled concrete decreased with increasing MSWI powder content.The amount of MSWI powder can affect the capillary height, absorption and crystallization rate of sulfate solution in concrete. The capillary rise height, osmotic crystallization rate and 5% sodium sulfate solution were linearly correlated with capillary porosity, but they were linearly independent of capillary porosity; thus, capillary porosity played a key role in capillary transport, migration and the crystallization of sulfate solution in recycled concrete.42−/Cl− erosion resistance of concrete.The MSWI powder had a certain strength activity, and it was feasible to replace part of the cement as a mineral admixture. It was not only beneficial to reduce the environmental problems caused by MSWI bottom slag, in line with the concept of green and sustainable development, but it also can make concrete more dense and improve the SOThe main conclusions of this paper are as follows:


In order to study the mechanical behavior and energy dissipation of architectural membrane materials under multistage cyclic loading, the deformation behavior, energy dissipation, and damage characteristics of four kinds of warp-knitted and woven polyvinyl chloride (PVC) membrane materials were analyzed using multistage cyclic loading experiments. The results show that, compared with the uniaxial tensile strength, the peak values of the cyclic loading and unloading of the four material samples are lower in the warp direction but higher in the fill (weft) direction. Under multistage cyclic loading, the loading and unloading moduli of the warp knitting membrane increase with the increase in fabric density. At the same fabric density, the loading modulus and the unloading modulus are smaller than those of the warp knitting material. The total absorbed strain energy, elastic strain energy, and dissipation energy of the fill samples are higher than those of the warp samples at a low load level but lower than those at a high load level. PVC membrane materials’ use strength should be controlled below a 15% stress level under long-term external force loading. In the cyclic loading process, the four PVC membrane materials are viscoelastic–plastic, so it is reasonable to define the damage variable based on the accumulation of plastic deformation. Flexible composites are generally made of two or more components with different thermal or mechanical properties and show great variations and complexity in tensile behavior compared to conventional material systems. Composite fabric reinforcements have a myriad of applications, including in the aerospace, automotive, and transportation areas ,2. Warp-Studies have found that the elastic modulus and residual deformation of polytetrafluoroethylene membrane materials, vinylidene fluoride/polyethersulfone membrane materials, and woven fabric-reinforced flexible composites are closely related to the number of repeated loading and unloading cycles ,13. It wCompared with a composite material with a woven structure, the warp-knitted biaxial structure has been used more and more as a reinforcement for flexible membrane composites due to the biaxial characteristics of the fiber arrangement direction ,20,21. MThe aim of this work is to investigate the mechanical properties of woven and warp-knitted PVC membrane materials under multistage cyclic loading. This paper focuses on the peak strength of the cyclic loading and deformation characteristics, the mechanics of elasticity, and fracture damage mechanic performance characteristics in order to compare the performances of the woven and warp-knitted PVC membrane materials. The advantages and disadvantages of the linear fitting and direct equivalent simulation are compared to calculate the loading and unloading moduli. Additionally, the macroscopic mechanical behavior, energy dissipation, and damage evolution were analyzed in order to further comprehend the behavior of the damage mechanics of the woven and warp-knitted PVC membrane materials. The knowledge obtained from these tests provides a better understanding of the performance and application of dynamically loaded flexible composites. It also provides a reference for their engineering application.Two flexible composites were selected as samples, and they were enhanced using polyester biaxial warp-knitted and woven fabrics . The warp and fill lining/yarns were 1000D/192F (111.11Tex) high-strength polyester industrial yarns. The specification of the binding yarn in the biaxial warp-knitted fabric was 75D/25F(83.33Tex) DTY polyethylene terephthalate (PET). Two types of fabric were bonded with a PVC membrane on both sides by the coating. The first type was a biaxial warp-knitted fabric with a tricot binding stitch, and the second type was a woven fabric with a plain weave construction.All samples were laminated with the same pure PVC membrane, and the coating thickness of each sample was the same. The 3 warp/weft laying yarn densities of the biaxial warp-knitted fabrics were 9 wales/inch and 9 courses/inch, 12 wales/inch and 12 courses/inch, and 18 wales/inch and 18 courses/inch. However, 1 fabric count (18 × 18 picks/inch) was selected to prepare the woven fabrics as controls. The specifications of the samples are listed in The width of the samples was (50 ± 0.5) mm, the length was (300 ± 0.5) mm, and the effective clamping distance was (200 ± 0.5) mm.1, K2, K3, and W1. In order to ensure that the samples were always in a state of tension during the experiment, the lower limit of unloading stress was the pre-tension level before the first cycle.In the multistage cyclic loading experiment, the automatic loading and unloading rate was 5 mm/min. There were 5 cyclic peak stress levels (100 times per level), which were 5%, 10%, 15%, 20%, and 25% of the samples’ fracture strength. The samples were named K1′, K2′, K3′, and W1′. All the experiments were carried out on the WDW-20 Hualong strength tester model at room temperature.In order to compare the strength characteristics of the PVC membrane materials under multistage cyclic loading, a uniaxial direct tensile fracture test was conducted on the warp and fill directions of samples; the loading speed was set at 10 mm/min, and these samples were named K2 (K1′), 40.03 N/mm2 (K2′), 46.73 N/mm2 (K3′), and 46.88 N/mm2 (W1′), and the average peak strengths of the multistage cyclic fracture are 22.39 N/mm2 (K1), 38.68 N/mm2 (K2), 45.19 N/mm2 (K3), and 40.99 N/mm2 (W1), which are 3.27–24.12% lower than the direct tensile fracture strength. The fill uniaxial tensile fracture strengths are 24.27 N/mm2 (K1′), 37.42 N/mm2 (K2′), 41.00 N/mm2 (K3′), and 42.35 N/mm2 (W1′), and the average peak tensile strengths of the multistage cycle are 24.97 N/mm2 (K1), 38.05 N/mm2 (K2), 47.29 N/mm2 (K3), and 49.55 N/mm2 (W1), which are 1.7–17% higher than the original tensile fracture strength.The stress–strain curves of PVC membrane materials under direct stretching and after multistage cyclic loading are shown in The fabric structure is greatly affected by the weaving and coating process; thus, in order to ensure a clear shed during the weaving process, the warp yarns were subjected to a higher tension and better elongation. In the process of coating, the warp yarns were also subjected to a higher tension, so they were further straightened and the degree of buckling was reduced. Under the action of the applied load, the warp strength utilization rate was higher, resulting in a higher direct tensile strength of the membrane materials .In the process of weaving and coating, the warp yarns were subjected to high tension and repeated tensile, bending, friction, and impact stresses, and the macromolecules in the fibers were fully straightened. During the multistage cyclic loading process, slips occur between macromolecules, resulting in a decrease in the intermolecular forces. Macroscopically, the peak strength of multistage cyclic loading is lower than the direct tensile fracture strength . However3 < K2 < K1, while the strain produced by warp knitting and woven materials with the same density is W1< K3 in comparison.It can be seen from 3 yarns is lower. Therefore, the viscoelastic deformation caused by the PVC resin on the surface of the K1 and K2 materials is more involved, resulting in a larger shape variation under the same stress level. Similarly, compared with the binding yarn gap caused by the warp knitting structure of K3, the yarns are more closely interwoven in the woven structure of W1, so the shape variable of W1 is smaller.The reason for this is that, according to the structural characteristics of the membrane material, the PVC resin coating on the surface of the membrane material is bonded to the surface of the base fabric by an adhesive, and the resin coatings on both sides are bonded to each other in the gap between the warp and the fill yarns. The PVC resin on both sides of the yarn interweaving point is bonded to the yarn in the base fabric. Due to the different adhesion of the interface, the void ratio between the high-density KIn the cyclic loading process, two main methods are used for calculating the elastic modulus of the loading and unloading: the linear fitting method and the approximate imitation method. In the linear fitting method, based on the initial stage of the loading and unloading stress–strain curves, the elastic modulus of loading and unloading can be obtained by linear fitting. This method can reflect the characteristics of the elastic modulus of materials. In the approximate imitation method, based on the slope of the connecting line of the initial loading point A and loading terminal B used to calculate the loading elastic modulus, and based on the slope of the connecting line of the initial unloading point B  and unloading terminal C used to calculate the unloading elastic modulus, the key step is to approximate the load and unload curves to a straight line. The slope of the straight line is the loading or unloading modulus of elasticity, which is shown in The multistage cyclic loading and unloading curves of both the fill and warp samples show obvious nonlinear characteristics. When calculating the elastic modulus of the loading and unloading, the slope of the line between points A and B is higher than that of the initial section of the curve AB, and the slope of the line between points B and C is also higher than that of the initial section of the curve BC. Compared with the linear fitting method, the elastic modulus of the loading and unloading calculated based on the approximate imitation method is higher and cannot objectively reflect the mechanical behavior of the materials.1 and K2 fill samples increase slightly with an increase in the number of cycles and those of the K3 and W1 decrease slightly. In the same cycle, the unloading modulus is higher than the loading modulus, and the difference between them first increases and then decreases with the increase in the number of cycles.Therefore, in this paper, the elastic moduli of the loading and unloading were calculated based on the linear fitting method, and their curves are shown in 3 > K2 > K1. At the same density, the loading and unloading moduli of the woven material are lower than those of the warp knitting material (W1 < K3). Under cyclic loading, the macromolecular chain of the reinforcing fiber and coating materials with a low adhesion slips first and provides a new combination with each other. As the macromolecular chain becomes straighter, the stresses improve, and the fiber deformation is mainly caused by the extension and retraction of the macromolecular chain. The aspect of macro performance evaluated is the modulus of elasticity increased.By comparing the factors that affect density, the values of the loading and unloading moduli increase with the increase in density, the order of which is KU is the total strain energy, mJ/mm3; Ue is the elastic strain energy, mJ/mm3; and dU is the dissipated energy, mJ/mm3.It is shown in The loading and unloading curves show hysteresis rather than coincidence loops, which is mainly due to the fact that PVC membranes are typical viscoelastic materials. During multistage cyclic loading, the material produces plastic deformation, so the hysteresis ring is not closed.The variation trends of the total absorbed strain energy, elastic strain energy, and dissipated energy of samples are shown in The total absorbed strain energy, elastic strain energy, and dissipated energy of the weft samples are lower when the cyclic load is the same. Taking the warp and fill samples of K1 for the second loading cycle as an example , due to 1, K2, K3, and W1 samples have the same variation rule; they all increase with the increase in density, and the fill direction value is larger than the warp direction. The comparison of woven and warp-knitted samples of the same density shows K3 > W1. 1, K2, K3, and W1 samples is relatively consistent, increasing with the increase in density, and, furthermore, the fill direction value is larger than the warp direction. The comparison of woven and warp-knitted samples of the same density shows K3 < W1.It can be seen from When the cyclic load peak level is low, the energy absorption and storage are mainly realized by the change of fabric structure and macromolecular conformation of the yarn and coating materials. The energy dissipation mainly comes from the slip of the macromolecular chains in the reinforcement fiber and coating material, the extension of the original damage and the destruction of the binding point between the coating and the reinforcement fiber.Due to the difference in strain in the manufacturing process of weaving and coating, relative to the warp yarns, the fill yarns’ macromolecular chain segments are in lower degrees, and the yarns’ extended degrees are insufficient. Under the applied load, the elongation of the fill yarns is mainly caused by a decrease in buckling and the macromolecular chain segments slipping; the fill elongations result in a lower modulus, so the fill samples may show a higher total absorption. In the recovery stage, the stretched macromolecular chain segments return to their initial state, the fill yarns have a degree of buckling, and their capacity for energy storage is stronger.In the cyclic loading process, the original weak areas are destroyed, and due to the great change in the fills’ buckling structure, the probability of failure of the bonding points between the reinforcement fibers and the coating materials is higher and is macroscopically expressed as the increase in dissipated energy.When the cyclic load peak level is high, the absorption, storage, and dissipation of energy are mainly dependent on the stretching, recovery, and slip of the macromolecular chains in the reinforced fiber and coating materials. The higher the load ratio is, the higher the degree of elongation of the macromolecular chain segment and the greater the degree of slip will be, while the recovery capacity will also be improved.Ue to the total absorbed strain energy U is defined as the energy rapid elastic recovery rate u, as follows:The ratio of the elastic strain energy u value of K1, K2, K3, and W1 tend towards 100% during the first 300 instances of multistage cyclic loading, and the fill samples’ u value of K1, K2, K3, and W1 tend towards 100% during the first 200 instances of multistage cyclic loading. When the warp samples are loaded at a 20% (400 cycles) stress level of the fracture strength of the sample, the u value decreases significantly, to 88% (K1), 91% (K2), 92.5% (K3), and 93.2% (W1). There was an overall trend of increase with the increase in density. When the fill samples of K2 and K3 are loaded at a 15% stress level (300 cycles), the u value decreases significantly to 85.6% (K2) and 82.5% (K3), while the u value of the fill samples of K1 and W1 decreases significantly when the samples are loaded at 20% stress level (400 cycles) and the rapid elastic recovery rate decreases to 91.5% (K1) and 90.8% (W1), respectively. The rapid elastic recovery rate of the four samples is higher in the fill direction than in the weft direction. The resilience of W1 is better than that of K3.dU is low, and most of the absorbed energy turns into elastic strain energy Ue. This shows that the energy consumption, which is caused by the expansion of the internal defects of the slip of the materials, fibers, and coating materials in the debonding of the macromolecular chain, fibers, and coating materials, is relatively small. It is mainly turned into the recoverable elastic strain energy Ue. With the increase in the multistage cyclic load peak, the dissipated energy dU increases, while the energy dissipation rate increases and reaches the maximum value when the cyclic load is in the range of a 15–20% stress level of the fracture strength. When the peak value of the cyclic load exceeds this critical value, although the dissipated energy continues to increase  When the material is under the action of cyclic loading, although there is no plastic deformation, actually the internal defects are produced. When the damage accumulation reaches a certain level, the damage in the material structure accumulates, and there is a failure in the material structural fatigue. (2) When the material is in an elastic–plastic working state, cyclic loading causes plastic deformation and also causes damage to the material. When the accumulated plastic deformation exceeds a certain limit, the service performance of the material is weakened until the failure limit appears.Du, during cyclic loading to the level i. The damage variable Du (i) can be represented as:U(t) is the total strain energy of the last stage cycle, in mJ/mm3.From the viewpoint of energy conversion, the accumulation of damage represents the energy dissipation, which can be defined as the damage variables from the perspective of energy dissipation. So, the division of the dissipation of energy, which is accumulated in the process of each cyclic loading to the final loading cycle dissipation, with the total strain energy results in the damage variable The relationship between the calculated damage variables and cyclic progression based on Equation (4) is shown in Dε(i) can be expressed as:bε is the fracture strain of the specimen under unidirectional tension, in mm/mm, and perε is the plastic deformation produced by each cycle, in mm/mm.From Dε, which is calculated based on Equation (5), and the number of cyclic loading instances is shown in The variation relationship between the damage variable Dε value of the damage variable, calculated based on the plastic deformation accumulation, is between 0 and 1; the four samples K1, K2, K3, and W1 satisfy this rule. So, within the range of the damage limit, it can be considered that it is reasonable to define the damage variable based on the plastic deformation accumulation [3 is higher than that of W1 from the difference in the fabric structure between the woven and warp-knitted fabrics.It can be seen from mulation . At the In this paper, four kinds of PVC membrane materials were tested and analyzed under multistage circulation. The deformation behavior and mechanism of warp-knitted and woven PVC membrane materials under multistage cyclic loading were studied and analyzed, especially in terms of the multistage damage characteristics under cyclic loading. The results of the experimental analysis are as follows.(1)1, K2, K3, and W1 samples is consistent, increasing with the increase in fabric density. Similarly, the fill values are larger than the warp values. According to the analysis of the energy dissipation rate, PVC membrane materials’ use strength should be controlled below a 15% stress level under long-term external force loading.For the four PVC membrane materials selected in this paper, the multistage cyclic fracture peak strengths of the warp-direction samples are lower than the original tensile strengths, while those for the fill-direction samples are higher than the direct tensile strengths, which is mainly due to the tension difference between the warp and weft yarns during weaving and coating processing. The overall trend of the dissipated energy of the K(2)3 > K2 > K1. At the same density, the loading and the unloading moduli of the woven material are lower than those of the warp knitting material (W1 < K3).The loading and unloading curves of the PVC membrane materials are obviously nonlinear, so it is more reasonable to use the linear fitting method to obtain the loading and unloading moduli compared with the approximate equivalent calculation method. For warp knitting materials, the loading and unloading moduli increase with the increase in density, and the values are K(3)Due to the peak strength of multistage cyclic loading being different from that of cyclic loading and unloading, the deformation processes of the warp and fill samples of the four kinds of PVC membrane materials are at different stages at the same cyclic loading times. However, the variation trends of energy and stress show the same law, that is, the total absorbed strain energy, elastic strain energy, and dissipation energy of the warp samples are higher than those of the fill samples under a low load level but lower under a high load level.(4)3 is higher than that of W1 for the same density of woven and warp-knitted membrane materials.Under multistage cyclic loading, the four PVC membrane materials are in the elastic–plastic deformation stage. It is more reasonable to define the damage variable based on the accumulation of plastic deformation than the change in elastic modulus and dissipation energy. Under the same cyclic load peak conditions, the damage levels of the fill samples are higher than those of the warp samples. The damage level of K


Germinal centers (GCs) are transient structures where affinity maturation of B cells gives rise to high affinity plasma and memory cells. The mechanism of GC shutdown is unclear, despite being an important phenomenon maintaining immune homeostasis. In this study, we used a mathematical model to identify mechanisms that can independently promote contraction of GCs leading to shutdown. We show that GC shutdown can be promoted by antigen consumption by B cells, antigen masking by soluble antibodies, alterations in follicular dendritic cell (FDC) network area, modulation of immune complex cycling rate constants, alterations in T follicular helper signaling, increased terminal differentiation and reduced B cell division capacity. Proposed mechanisms promoted GC contraction by ultimately decreasing the number of B cell divisions and recycling cells. Based on the in-silico predictions, we suggest a combination of experiments that can be potentially employed by future studies to unravel the mechanistic basis of GC shutdown such as measurements of the density of pMHC presentation of B cells, FDC network size per B cell, fraction of cells expressing differentiation markers. We also show that the identified mechanisms differentially affect the efficiency of GC reaction estimated based on the quantity and quality of resulting antibodies. Germinal centers (GCs) are highly organized structures in secondary lymphoid organs that support affinity maturation of B cells by iterative rounds of mutation and selection . A maturThis evolutionary process of B cells lasts only for a limited period of time as GCs are transient and undergo shutdown. The lifetime of single GCs in a lymphoid organ is unknown, but collective GC responses in a lymphoid organ lasts for a period of 3 weeks in the case of model protein antigens and more than a month in chronic viral infections –14. TherGC contraction occurs due to a shift in the balance between proliferation, apoptosis and terminal differentiation of B cells when apoptosis and differentiation overtake the proliferation . These aThese experimental observations suggest the role of different cell types and B cell intrinsic factors in controlling GC maintenance but the exact mechanism behind natural GC shutdown is unknown . NeverthPoor understanding of GC shutdown is partly due to technical challenges and complex behavior of GCs. Mathematical modeling was an integral part of GC research and contributed to our understanding of the mechanisms behind GC B cell selection , 35, prehyphasma  delivered to the B cell is a function of pMHC presentation p and calculated asThe Tfh signaling intensity was assumed to depend directly or only indirectly on the pMHC presentation of GC B cells. In the first scenario, upon successful polarization, Tfh signals Jmin = 0, Jmax=3, n = 2 and Kp =7.1.with J = 1). For direct and indirect dependency, the Tfh cell polarizes towards the B cell that has highest pMHC presentation in the presence of multiple interacting B cells leading to an indirect dependence of Tfh signals on antigen collected under conditions of high B cell competition for Tfh help.For the indirect dependence, Tfh signals delivered to the B cell is simply a measure of the time period during which the Tfh cell is polarized to the B cell  corresponds to a different koff and same kon thus leading to different affinities such that the dissociation constant is in the range of 10-5.5 to 10-9.5 M. Antibodies were assumed to undergo degradation with a rate constant of A(i) is diluted over a volume V of 10 ml, as it is assumed to distribute throughout the circulatory system and is calculated as follows.Output cells exiting the GC area were assumed to differentiate into plasma cells with a rate constant corresponding to a half-life of 24 h. Plasma cells secrete antibodies at a rate of per cell . Antibodnp(i) is the number of plasma cells with affinity corresponding to bin i.In this equation, GFDC, while dissociation of antibody increases the concentration of free antigen. Changes in the concentration of soluble antibodies by the formation of ICs is neglected. The rate of change of masked antigen concentration CFDC followsMasking of antigen by antibodies in Equation 4 leads to a decrease in the free antigen concentration N) is used to modulate the concentration of antibodies promoting feedback in the above equation. This scaling factor can be interpreted as the number of synchronously initialized GCs   Asurfackext is assumed to be modulated in a time t dependent manner according toAs the GC progresses, kext , the time point where kext (t) = kext (0)/2, was varied  in the simulations. In the control simulation, kint and Kext remain constant throughout the GC reaction.with the Hill coefficient n= 2. Tmax is assumed to decrease according to the following Hill function in a time dependent manner t.The intensity of the maximum Tfh signaling n=2. KT, the time point where Tmax(t) = Tmax(0)/2 , was varied  to adjust the speed of GC contraction. In the control simulation, the Tfh signaling intensity is assumed to be constant throughout the simulation.with F, without recycling to the DZ for cell cycle re-entry. Different possibilities were considered for this mechanism, where the terminal differentiation in the LZ is antigen uptake (p), Tfh signal (Tsig) or time dependent (t). In antigen uptake and Tfh dependent terminal differentiation, the probability of differentiation was calculated according toTfh selected cells were assumed to differentiate to output cells and exit the GC with probability X=p and Tsig, respectively, and n=2. The value of KF  was varied in the simulations. In time dependent (t) terminal differentiation, the probability of terminal differentiation followswhere k  was varied to adjust the speed of GC shutdown. In the control simulations, F=0 and therefore, 100 % of selected cells recycle back to the DZ for cell cycle re-entry.where The number of divisions of GC B cells was assumed to depend on the number of DZ-LZ cycles underwent, in addition to the dependence on antigen uptake and Tfh signals acquired.K in Equations 1 and 2 was assumed to be a function of the number of DZ-LZ cycles Ncyc and calculated asThe value of K is minimum Kmin at the start of the simulation. In the control simulation, the value of K remains constant and equal to Kmin throughout the simulation. We used n=2, Kmin = 1, 1, 0.5, 0 in A1-A4, respectively, and Kmax = 25, 25, 4.5, 6 in A1-A4, respectively. The value of KK  was varied in the simulations.The value of The average number of divisions of selected or recycled B cells were calculated at one-hour time windows during the course of the reaction.R =10-5 M was considered. The fraction of test antigen bound Rbound by soluble antibodies A(i) produced from the GCs was calculated using the following steady state approximation which assumes that the concentration of test antigen is much higher than the concentration of antibodies:To calculate Immune Power (IP) or efficiency of GC reactions , 54, a tin-silico simulations by implementing seven different mechanisms of GC shutdown , antigen limitation is due to a reduced number of B cell- FDC encounters. However, in the other antigen limitation mechanisms there is a decrease in the number of B cell-FDC encounters with successful antigen capture S5-S7B. FDC-B cell interactions and antigen capture of naïve B cells in primary follicles have been visualized by two-photon microscopy with Phycoerythrin-labelled antigen and CFSE/CFP labelled B cells . A similThe FDC network size per B cell was calculated by dividing the total number of lattice sites occupied by the FDC network by the total number of GC B cells, which can be interpreted as a measure for the GC space occupied by FDCs.In the absence of FDC contraction, the FDC network size per B cell decreases until the GC volume attains a peak and increases thereafter. However, in the presence of FDC contraction, the FDC network size per B cell decreases or remains constant after the peak of the GC reaction S5–S7C. The IC cycling rate constants determine the fraction of ICs on the FDC surface which is defined as the ratio of IC amount on the FDC surface, and the total antigen amount retained in the FDC. The fraction of ICs on the FDC surface is expected to remain constant if the IC cycling rate constants are constant throughout the GC reaction. Modulations of IC cycling rate constants as proposed in mechanism M4 will lead to differences in the distribution of ICs on the FDC’s surface and interior during the GC reaction such that the fraction of ICs on the FDC surface decreases over time S5-S7 D.In mechanism M5, due to reduced Tfh signaling, a decrease in Tfh signals acquired by GC B cells was observed over time S5-S7E. However, in assumptions A1 and A4, only a subtle decrease in Tfh signals was seen that was not statistically significant. In addition, a decrease in Tfh signals is also seen in the case of antigen limitation models depending on the assumptions  that mimics an ELISA test , 54. Mecin-silico, to identify the most promising target mechanisms that are self-sufficient to contract GCs. To facilitate experimental analysis of these mechanisms, we suggest potential experimental setups based on the in-silico predictions.Although GC shutdown is an important determinant of the quality and quantity of antibody responses, mechanisms of GC shutdown are poorly understood. Premature GC shutdown can impair the protection against invading pathogens or reduce the efficacy of vaccinations and lack of GC shutdown has the potential to give rise to GC-derived B cell lymphomas. Thus, a better understanding of GC shutdown has a wide range of applications from enhancing antibody responses to blocking the progression of B cell lymphomas and ectopic GCs. In this study, we tested potential mechanisms of GC shutdown In all of the mechanisms identified, from antigen limitation to reduced B cell division capacity, GC shutdown was ultimately caused by a decrease in either the number of B cell divisions or reduced recycling to the DZ or both. Gitlin et al., demonstrated that GC B cell divisions are proportional to antigen uptake and pMHC presentation to Tfh cells . But, thFurthermore, outcome of the shutdown mechanisms was sensitive to the set of assumptions considered for the determinants of Tfh signal intensity and the number of B cell divisions. Although there is considerable evidence for the dependence of productive B-Tfh cell interactions on pMHC presentation , the extIn-silico simulations suggested the potential of antibody feedback in terminating GCs. Antibody feedback as a mechanism of GC shutdown is an attractive option because it self-regulates the necessity of continuation of the GC response by monitoring success of the GC reaction right in the GC area. Dynamic changes in FDC network by the contraction of FDCs  can be found below: Code and scripts used in this study are available at Zenodo: TA, SB, and MM-H designed the study. TA performed simulations. SB and MM-H supervised the project. TA, SB, and MM-H wrote the manuscript. All authors contributed to the article and approved the submitted version.TA was supported by the European Union's Horizon 2020 research and innovation programme COSMIC under the Marie Sklodowska-Curie grant agreement no. 765158.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


The physical activation of the precursor led to the strongly basic character of the surface. Chemical activation with 50% solution of H3PO4 of the residue of supercritical extraction of green tea leaves promoted the generation of acidic functional groups. All adsorbents were used for methylene blue and methyl red adsorption from the liquid phase. The influence of the activation method, pH of the dye solution, contact time of adsorbent with adsorbate, the temperature of adsorption, and rate of sample agitation on the effectiveness of organic dyes removal was evaluated and optimized. In the process of methylene blue adsorption on adsorbents, an increase in the sorption capacity was observed with increasing pH of the adsorbate, while in the process of methyl red adsorption, the relation was quite the reverse. The adsorption data were analyzed assuming the Langmuir or Freundlich isotherm models. The Langmuir model better described the experimental results, and the maximum sorption capacity calculated for this model varied from 144.93 to 250.00 mg/g. The results of the kinetic analysis showed that the adsorption of organic dyes on activated carbon was following the pseudo-second-order model. The negative values of the Gibbs free energy indicate the spontaneous character of the process.Activated carbons were obtained by physical and chemical activation of the residue of supercritical extraction of green tea leaves. All the adsorbents obtained were characterized by: elemental analysis, low-temperature nitrogen adsorption, and the contents of acidic and basic oxygen functional groups on the surface of activated carbons by the Boehm method. The activated carbons were micro- or micro-mesoporous with well-developed surface area ranging from 520 to 1085 m When taking into account the high biotoxic effect of sewage , both muOne of the most popular adsorbents used for the removal of liquid pollutants of either organic or inorganic origin is activated carbon ,8. MaterThe properties of activated carbon-based adsorbents depend on the type of source of carbon used, so the first step in the search for the right adsorbent is a careful choice of the raw material, the method of activation, activating factor, and conditions of carbonization and activation ,19.3PO4 is the possibility of using lower temperatures than in the processes with other activating agents. The process of physical activation involves two subprocesses: pyrolysis of the precursor followed by its activation ; n—the Freundlich constant describing intensity of adsorption; FK—the Freundlich constant describing adsorption capacity (mg/g(mg/L)1/n).The results were interpreted assuming the following four models of adsorption: Freundlich, Langmuir, Temkin, and Dubinin–Radushkevich . The linLK—the Langmuir equilibrium constant (L/mg).The Langmuir model refers to the adsorption of a single layer on the adsorbent surface. The linear form of this model (3) can be written as:LR) known as the equilibrium parameter (4):The Langmuir isotherm is also characterized by the dimensionless constant (LR = 1)—linear; (LR ≥ 1)—unfavorable; (0 < LR > 1)—favorable; (LR = 0)—irreversible.Its value informs about the shape of the Langmuir isotherm: ; R—gas constant (J/mol × K); T—temperature (K); TA—Temkin isotherm equilibrium binding constant (L/mg).Another model describing the process of adsorption has been proposed by Temkin (5) and is described by the equation:mq—the monolayer adsorption in the Dubinin–Radushkevich model (mg/g); β—a constant describing the sorption energy (mol2/kJ2); ε—adsorption potential.The last model taken into consideration in this study has been proposed by Dubinin–Radushkevich (6) and is given by the equation:β it is possible to find the free energy of adsorption E (kJ/mol), (7):On the basis of the value of E < 8 kJ/mol the mechanism involves physical interactions, if E comes from the range 8–16 kJ/mol, the dominant mechanism is based on ion exchange, while E > 16 kJ/mol indicates that the molecules undergo diffusion in the process of adsorption.The mean free energy gives information about the type of adsorption, chemical or physical, taking place. If tq—the amount of dye adsorbed in a given time (mg/g); k1—the adsorption constant in the pseudo-first-order equation (L/min); k2—the adsorption constant in the pseudo-second-order equation (g/mg × min).In order to check the effect of contact time on the effectiveness of the adsorption of the dyes studied, glass bottles were charged with 20 mg of selected activated carbon flooded with 50 mL of either methylene blue (80 mg/L) or methyl red (50 mg/L). The loaded bottles were shaken on a shaker working at the speed of 200 rmp/min. At selected time intervals , the absorbance of the solution was measured. The kinetics of adsorption at the dye/activated carbon interface was approximated by two empirical equations, the Langergen one (8) (pseudo-first-order) and Ho and McKay one (9) (pseudo-second-order) ,34:(8)lnThe relation between the sorption properties of the activated carbon samples and pH of the dye solution was examined for pH, ranging from 2 to 12. The pH values of the water solutions of methylene blue and methyl red were changed by addition of 0.1 M of NaOH/HCl solution. The samples AC and AF flooded with dye solution of appropriate concentration and pH were agitated (200 rmp/min) for 300 min. Measurements were performed for 20 mg of the activated carbon and 50 mL of the dye solution of an appropriate concentration  and pH in the range 2–12.G—Gibbs free energy (kJ/mol); ΔS—entropy (kJ/K × mol); ΔH—enthalpy (kJ/mol); T—absolute temperature (K); R—gas constant (8.3144 J/K × mol); dK—the equilibrium constant equal to eq/eC.Thermodynamic studies were carried out in the temperature variants: at 25, 45 or 65 °C. The glass bottles loaded with the samples were shaken (200 rmp/min) and heated for 300 min. The procedure of sample preparation was the same as that used when studying the effect of pH of the dye solution on the adsorption capacities of the carbon adsorbents. The thermodynamics of the adsorption of the dye on the activated carbon adsorbents was characterized on the basis of the enthalpy, entropy, and Gibbs free energy, calculated from the following Equations (10) and (11):Analysis glass bottles were loaded with different amounts of the two types of activated carbon adsorbents: 10, 20, and 30 mg, and flooded with 50 mL of methylene blue (80 mg/L) or methyl red (50 mg/L). The charged bottles were shaken at the speed of 200 rmp/min for 300 min; then, spectrophotometric measurements were made.The impact of agitation rate on the sorption capacities of the adsorbents studied was checked for two agitation rate values 100 or 200 rmp/min. The process of agitation at a given rate was carried out for 300 min for the samples containing 20 mg of a given activated carbon and methylene blue in a concentration of 80 mg/L or methyl red in a concentration of 50 mg/L.A good precursor of activated carbon should first of all be characterized by a low content of ash and a high content of elemental carbon. As activated carbon adsorbents are in high demand because they are needed in large amounts for the removal of liquid and gas phase pollutants, their popular precursors are cheap materials, often agricultural waste products . A wide Only walnut shells  have oveThe specific surface area, pore volume, and average pore diameter were determined by the BET method. The obtained values of the above parameters are collected in 2/g, which is almost twice greater than that of the sample obtained by physical activation (AF) of 520 m2/g. The total pore volumes determined for the two samples are similar and fit in the range of 0.62–0.64 cm3/g (see 3PO4) shows a distinctly microporous character (1.9 nm), and the average diameter of its micropores is <2 nm. The value of the average pore diameter for the sample obtained by physical activation, AF, is 4.1 nm. The data presented in 2/g) has better textural properties than the activated carbon obtained with the use of a tube furnace (250 m2/g), as described in another scientific paper [The specific surface area of the carbon adsorbent obtained by chemical activation, sample AC, is 1085 mm3/g see . The dific paper .As expected, irrespective of the method of activation, the obtained activated carbons showed a much higher content of elemental carbon than the precursor .daf 1.4–1.6% wt. and Ndaf 0.5–0.9% wt.) relative to their content in the precursor  obtained by physical activation. The higher content of elemental carbon in sample AF may be a consequence of a relatively high activation temperature and a long time of the process, which could stimulate the aromatization of the carbon structure. When using microwave heating, usually, a lower temperature is applied. The increase in the content of elemental carbon resulted in a decrease in the content of hydrogen and nitrogen over acidic (0.8 mmol/g) ones was found. The Boehm titration-based conclusions were confirmed by measurements of pH of water extracts of the adsorbents studied, equal to 4.6 and 10.8 for samples AC and AF, respectively.The results indicate that the chemical character of the surfaces of the activated carbon depends on the method of obtaining the carbon adsorbents. The activation of precursor with a 50% solution of HThe results of sorption capacity measurements towards water solutions of the two organic dyes obtained for the activated carbon samples AC and AF are presented in a bar diagram .According to these results, the sample obtained by chemical activation proved to be a more effective adsorbent of the dyes. Its sorption capacity towards a water solution of methylene blue is 248 mg/g , while towards methyl red, it is 163 mg/g . The sample obtained by physical activation of the residue of supercritical extraction of green tea leaves has an adsorption capacity of 160 mg towards methylene blue and 136 mg towards methyl red. The higher sorption capacity of sample AC is a consequence of a much better developed specific surface area of this sample relative to that of sample AF. A comparison of the data presented in 2, the Langmuir model proved to better describe the data obtained for adsorption of a water solution of methylene blue; the value of R2 for sample AC was 0.9986, while for sample AF, it was 0.9913. The highest values of the correlation coefficient for the Langmuir equation obtained for AC and AF indicate that this isotherm provides the best description of methylene blue adsorption. Thus, adsorption of methylene blue on samples AC and AF involves the formation of a monolayer on their surfaces, and the maximum sorption capacity of the monolayer, qmax, is close to the experimentally determined sorption capacity , were obtained for the Freundlich model.capacity . For theL obtained for both samples, AC and AF, irrespectively of the dye adsorbed, takes values from the range 0–1 , which favorable adsorption [m parameter obtained for the Dubinin–Radushkevich model are lower than the qmax determined for the Langmuir model. The value of qm informs about the maximum amount of adsorbed adsorbate by a given adsorbent in the volume of its micropores [According to the data presented in sorption . From thsorption . The enecropores .The knowledge of the effect of contact time of adsorbent with adsorbate on the effectiveness of adsorption permits the determination of the optimum time of shaking off the adsorbent/adsorbate system to reach equilibrium. The data illustrating this effect are collected in 2 was obtained for samples AC  and AF , assuming the pseudo-second-order process suggests the chemisorption of the dyes [e,exp parameter, and its value calculated for the Ho and McKay model supports the use of the model for the description of the adsorption of water pollutants on adsorbents obtained from residues of supercritical extraction of green tea leaves.On the basis of the results obtained in the experiment checking the effect of contact time on the sorption capacities of samples AC and AF, the kinetic parameters of adsorption were calculated assuming the Langergen model (8) (pseudo-first-order) and Ho and McKay model (9) (pseudo-second-order). The parameters are given in the dyes . InteresThe pH value of the water solutions of the dyes is expected to have a significant effect on the effectiveness of their adsorption . The meaIn order to assess the effect of temperature on the sorption capacities of the adsorbents studied, the measurements of absorbance were performed in three temperature variants: at 25, 45, or 65 °C. The results are given in The effect of temperature on the effectiveness of the adsorption of the dye was found to be insignificant. The character of the curves obtained a,b indicAs can be concluded from the analysis of these data, with increasing dosage of the adsorbent, the sorption capacity decreases. It can be explained by the decreased ratio of the amount of the dye to the mass unit of the adsorbent, which leads to a decrease in the coefficient describing the use of active sites . It has Moreover, the effect of the agitation rate on the sorption capacities was also checked, and the results are presented in The above-described results have confirmed that the method of microwave heating can be successfully applied for obtaining activated carbon-based adsorbents of organic dyes from water solutions. According to the obtained BET results, the adsorbents produced from the residue of supercritical extraction of green tea leaves have a well-developed specific surface area of micro- or micro-mesoporous character. The Langmuir model has better described the experimental results, and the maximum sorption capacity calculated for this model varied from 144.93 to 250.00 mg/g. In order to reach the state of adsorption equilibrium, the process of adsorption of organic dyes from their water solutions should be performed for 5 h, and the kinetics of the process corresponds to the pseudo-second-order model. The negative values of the Gibbs free energy indicate the spontaneous character of the process.