Degree Of Aggregation Research Articles

Rumor detection model with weighted GraphSAGE focusing on node location

While social media platforms promote people’s information exchange and dissemination, they also make rumors spread rapidly on online platforms. Therefore, how to detect rumors quickly, timely and accurately has become a hot topic for scholars in related fields. Traditional deep learning models ignore the relationship and topology between nodes in the rumor detection task and use fixed weights or mean aggregation strategies in the feature aggregation process, which fail to capture the complex interactions between nodes and the dynamics of information propagation, limiting the accuracy and robustness of the rumor detection model. To address these problems, we propose a location-aware weighted GraphSAGE rumor detection model GSMA. We first introduce an attention mechanism that dynamically assigns different attention weights to different neighboring nodes for different degrees of aggregation, improving GraphSAGE’s strategy of using mean-value aggregation for all neighboring nodes during the aggregation process; second, we introduce a modulated position encoding into the model and encode the position information of nodes into the features to improve the model’s ability to perceive the relative position and order of nodes; finally, the post text sentiment is incorporated into the features to provide additional semantic information for the model as a way to achieve rumor detection in microblogging platforms. Experiments show that the accuracy of the GSMA model on Ma-Weibo and Weibo23 reaches 97.43% and 97.55%, which is an improvement of 1.11% and 0.77% compared to the benchmark GraphSAGE, and all the evaluation metrics are also improved compared to other optimal rumor detection models.

Nonlinear Radiative Response to Patterned Global Warming due to Convection Aggregation and Nonlinear Tropical Dynamics

Abstract Climate responses to global warming exhibit large dependence on the spatial pattern of sea surface temperature (SST) changes. A Green’s function (GF) approach—predicting the global climate response to a complex SST pattern change as the linear superposition of the response to finite-area SST perturbations evaluated in isolation—has been used to systematically evaluate and understand the top of atmosphere (TOA) radiation response to patterned warming. However, in general, the linear GF approach fails for TOA radiation reconstruction under future global warming scenarios in coupled models. Here, we show that the linear superposition of global mean TOA radiation responses to large SST warming perturbations at multiple patches (the GF approach prediction) overestimates the actual response to simultaneous multipatch perturbation. This is because the linear superposition overestimates tropical large-scale convection aggregation strengthening upon localized heating that enhances longwave radiative cooling, which is further explained by the overestimation of circulation response and associated horizontal water vapor transport. The nonadditivity of TOA radiation response is caused by the nonadditivity of convection aggregation, ultimately rooted in nonlinear tropical dynamics. We also demonstrate that the prediction error of the GF approach grows with decreasing patch size (equivalently, increasing patch number). We conclude that using the GF approach to predict future climate change could overestimate longwave radiative cooling and underestimate (effective) climate sensitivity. Numerical experiments may be used to identify specific perturbation patterns where the errors are smaller than the signal. Our research also highlights that an increase in the degree of large-scale convection aggregation has a nonlinear and negative feedback for mean warming.

Antidehydration and Stable Mechanical Properties during the Phase Transition of the PNIPAM-Based Hydrogel for Body-Temperature-Monitoring Sensors.

Poly(N-isopropylacrylamide) (PNIPAM) enhances the reversibility and responsiveness of wearable temperature-sensitive devices. However, an open question is whether and how the hydrogel design can prevent adhesive performance loss caused by phase-transition-induced dehydration and unstable mechanical properties between devices and human skin and reduce interfacial failure. Herein, a gelatin-mesh scaffold-based hydrogel (NAGP-Gel) is constructed to inhibit dehydration and volume change, leading to stable mechanical properties, superior adhesiveness, and thermal sensing sensitivity during the phase transition. NAGP-Gel enhances the polymer chains-water interaction and weakens the degree of aggregation of polymer chains-chains, improving antidehydration properties under 45 °C conditions that are higher than the lower critical solution temperature (LCST; i.e., ∼32 °C). The mesh scaffold greatly restricts the phase-transition-induced polymer chain movement and maintains the mechanical performance. In a 60 °C environment, the maximum water loss and volume retention ratio of NAGP-Gel are only 3.58% and 97.3%, respectively. Additionally, NAGP-Gel serves as a temperature sensor, producing a stable thermal-electrical signal within the LCST range. It also can be assembled into an electronic device enabling the transmission of information and recognition of sign language via Morse code. This work broadens the application of PNIPAM in constructing intelligent hydrogels and opens the door to exploring emerging hydrogels for temperature-monitoring applications.

Role of inclusion clusters on fatigue crack initiation in powder metallurgy nickel-based FGH96 superalloy

Inclusion clusters with a size of several tens of micrometers were found to be inclined to early crack initiation, resulting in an abnormally reduced fatigue life. Fatigue tests were conducted to elucidate crack initiation behaviors of inclusion clusters in nickel-based powder metallurgy (P/M) FGH96 superalloy. The inclusion clusters with varying sizes and shapes located at grain boundaries are composed of Al2O3, MgO and ZrO2 particles. The inclusion cluster with large size within 25-35 μm, small average particle distance within 0-4 μm and large orientation relative to loading direction within 35-66° will be more likely to cause crack initiation. In particular, the inclusion clusters with large size and high aggregation degree experience extruding during processing and subsequent heat-treatments due to the difference in thermal expansion coefficient with the matrix behave multiple cracking before fatigue loading, thereby facilitating crack initiation in the surrounding matrix grains. Moreover, as the main cracking part of inclusion clusters, the Al2O3 particles exhibit self-cracking and interface debonding, owing to higher hardness and poorer deformation coordination degree with matrix compared to other component inclusion particles.

Spatiotemporal Relationship Between Land Subsidence and Ecological Environmental Quality in Shenfu Mining Area, Loess Plateau, China

The exploitation of coal resources has caused problems such as ground deformation, affecting the ecological environment. Spatiotemporal varying characteristics between land subsidence and ecological environmental quality (EEQ) are an important research hotspot. Using the SBAS-InSAR method, 64 Sentinel-1 images were utilized to monitor land subsidence in the Shenfu mining area, one of China’s largest coal source regions. And the remote sensing ecological index (RSEI) was used to monitor and evaluate EEQ of the Shenfu mining area. Global and local spatial autocorrelation methods were used to assess the spatial aggregation degree and change patterns over time. Spatial Econometric Models were employed to explore the impacts of land subsidence on EEQ. The results showed the following: (1) The average RSEI values in the Shenfu mining area were 0.531, 0.488, and 0.523 in 2016, 2018, and 2020, respectively; there was a slight downward trend in EEQ. The permanent scatter (PS) point deformation rate ranged from −353.40 mm/year to +246.24 mm/year, with average deformation rates of 0.1642, 0.2181, and 0.2490 mm/year, respectively. (2) There was a significant correlation and spatial agglomeration effect between land surface subsidence and EEQ. Low–high, high–low, and low–low clusters were the main types of relationships, indicating that land subsidence primarily has a negative spatial impact on the ecological environment. (3) The relationship between land subsidence and EEQ varied spatially in the Shenfu mining area at 500 × 500 grid units. This research can provide scientific guidance for disaster prevention and sustainable development in mining areas by considering long-term differences in ecological environmental quality and its correlation with land subsidence.

Regulation on Aggregation Behavior and In Vitro Digestibility of Phytic Acid-Whey Protein Isolate Complexes: Effects of Heating, pH and Phytic Acid Levels.

The impact of heat treatment, pH and phytic acid (PA) concentration on the aggregation behavior and digestibility of whey protein isolate (WPI) was investigated. The experimental results indicated that below the isoelectric point of WPI, heat treatment and elevated PA levels significantly increased turbidity and particle size, leading to the aggregation of WPI molecules. No new chemical bonds were formed and the thermodynamic parameters ΔH < 0, ΔS > 0 and ΔG < 0 suggested that the interaction between PA and WPI was primarily a spontaneous electrostatic interaction driven by enthalpy. After the small intestine stage, increasing phytic acid levels resulted in a significant decrease in hydrolysis degree from 16.2 ± 1.5% (PA0) to 10.9 ± 1.4% (0.5% PA). Conversely, above isoelectric point of WPI, there was no significant correlation between the presence of PA and the aggregation behavior or digestion characteristics of WPI. These results were attributed to steric hindrance caused by PA-WPI condensates, which prevented protease binding to hydrolysis sites on WPI. In summary, the effect of PA on protein aggregation behavior and digestive characteristics was not simply dependent on its presence but largely on the aggregation degree of PA-WPI induced by heat treatment, pH and PA concentration. The findings obtained here suggested that phytic acid may be utilized as an agent to modulate the digestion characteristics of proteins according to production requirements. Additionally, the agglomerates formed by heating phytic acid and protein below the isoelectric point could also be utilized for nutrient delivery.

Effect of Shikimic Acid on Oxidation of Myofibrillar Protein of Duck Meat During Heat Treatment.

The myofibrillar protein (MP) of duck meat is prone to excessive oxidation during thermal processing, resulting in a decline in its overall quality. In this paper, the effect of shikimic acid on the oxidative structure of duck muscle fibrin was studied. The findings showed that, at a mass ratio of 1:50,000 (g/g) between shikimic acid and MP, the carbonyl content of MP was reduced by 74.20%, while the sulfhydryl content was increased by 73.56%. MP demonstrated the highest denaturation temperature, whereas its thermal absorption was the lowest. The percentage of α-helixes and β-sheets increased by 16.72% and 24.74%, respectively, while the percentage of irregular structures decreased by 56.23%. In addition, the surface hydrophobicity index of MP exhibited a significant decrease (p < 0.05), while there was a significant increase in its free radical-scavenging ability (p < 0.05). Molecular fluorescence spectrum analysis showed that shikimic acid could bind to MP, altering the internal environment of MP and enhancing its thermal stability. FTIR analysis showed that shikimic acid could enhance the distribution of protein particle sizes by reducing irregular structures, the proportion of β-rotation, and the degree of protein aggregation. It is hoped that this research can offer scientific support for improving meat processing technology.

Research on Spatial Data Aggregation Based on Aggregation Degree Function

Abstract. Restricted by the development level of hardware and software technology, computers cannot load massive data at one time, coupled with the fact that the three-dimensional linear scene is characterized by complicated lines, irregular shapes of features and a large number of features. Therefore, it is necessary to seek a three-dimensional spatial data organization and scheduling method applicable to the railroad scene to realize the display and interaction of the scene. In this paper, we propose a data organization method based on the aggregation degree function for the 3D model of features. The feature model is projected to generate an orthographic projection map, the cluster division rule is designed to divide the subsets, the feature model after clustering is aggregated using the feature model aggregation rule, and the aggregated model is displayed according to the aggregation degree function and viewpoint factor. The results of the test applied to the railroad scene show that the 3D spatial data aggregation based on the aggregation degree function can improve the loading speed of the 3D scene, and can effectively support the application of interactive visualization of the railroad 3D scene.

Effect of Aspect and Elevation on the Degree of Aggregation and the Functional Traits in Phlomis floccosa D. Don (Lamiacae) Populations

ABSTRACTPhlomis floccosa D. Don populations are distributed in different microhabitats within Al‐Akhdar mountainous landscape, in Libya. Five populations were selected for the study. Spatial relationships among individuals were investigated using the spatial point pattern analysis. Functional traits were recorded at the vegetative, flowering and fruiting stages. Seeds were collected at the dispersal stage to estimate the regeneration potential. Greater degree of aggregation was found at higher elevations on both northern and southern sides of the mountain but with different demography and traits. On the northern side, greater degree of aggregation was accompanied by absence of large adults and greater percentage of seedlings, and it was positively associated with the reproductive output, while negatively associated with the size and regeneration indices. On the southern side, greater degree of aggregation was accompanied by greater contribution of large adults and greater percentage of seedlings, and it was positively associated with the size and regeneration indices, while negatively associated with the reproductive output. On the other hand, the population in the wadi (valley) microhabitat showed coarse‐scale clumped pattern, higher values for most of the functional traits and higher contribution of seedlings but with lower facilitation offered by adults. The variations in the degree of aggregation and the functional traits trade‐offs in P. floccosa populations ensured successful survival and regeneration in the heterogeneous microhabitats. Meanwhile, stressed conditions greatly affect the survival and regeneration of the species suggesting the need for conservation measures to overcome the adverse effects of climate change.

Intraoperative Bleeding Model for Swine Gastric Endoscopic Submucosal Dissection Via Heparinization

Background: Living swine has a high degree of coagulation and aggregation, and training for managing intraoperative bleeding during endoscopic submucosal dissection (ESD) is unsatisfactory. This study aimed to identify the appropriate heparin dose in an intraoperative bleeding model and validate its applicability. Methods: First, we explored the dose of heparin required for a swine bleeding model in which the activated clotting time reached and maintained the upper limit of measurement (1500 s) after 10 min. Second, we compared intraoperative bleeding and hematoma frequency during ESD for 2 cm lesions between the heparinized bleeding model and control groups. Intraoperative bleeding was classified according to the Forrest classification. Results: The combination of a bolus (300 U/kg), continuous infusion (300 U/kg/h), and a bolus dose (150 U/kg) of heparin 10 min after the first infusion was identified as the dose of the bleeding model. Five ESDs were performed in each heparinized bleeding model and the control group. The median number of intraoperative bleeding was significantly higher in the heparinized model than in the control group (5 [interquartile range {IQR}, 4–7] vs. 3 [IQR, 0–4], p = 0.028). All intraoperative bleeding events were not spurting (Forrest Ia) but oozing (Forrest Ib). The median number of hematomas was significantly higher in the heparinized model group than in the control group (3 [IQR, 1–4] vs. 0 [IQR, 0–1], p = 0.023). Conclusion: High doses of heparin significantly increased intraoperative bleeding and hematoma during swine ESD.

Unravelling structural insights into ligand-induced photoluminescence mechanisms of sulfur dots.

Sulfur dots (S-QDs) hold promise as a new category of metal-free, luminescent nanomaterials, yet their practical application faces challenges primarily due to a limited understanding of their structure and its impact on their optical properties. Herein, by employing a spectrum of aliphatic and aromatic ligands, we identify the surface structure and composition of S-QDs while delineating the pivotal role of ligands in inducing photoluminescence. Thiol-functionalized ligands, such as 4-mercapto benzoic acid and glutathione, notably promote the formation of both green and blue luminescent S-QDs, boosting a high quantum yield of up to 56%. Further investigation on the synthesis of S-QDs with 4-mercapto benzoic acid unveils the dual role of H2O2: etching sulfur powder and oxidizing the -SH group to -SO2H. These oxidized ligands passivate the S-QD surface through hydrogen bonding. Electrospray ionization mass spectrometry analysis unveils the presence of distinct sulfur species such as [S4(C6H5SO2H)4(H2O)2H]+ and [S6(C6H5SO2H)6(H2O)3H]+, while XPS analysis confirms the existence of zerovalent sulfur and oxidized sulfur species including SO32- and SO42-. Further detailed spectroscopic examination demonstrates that S-QDs predominantly exist as aggregated entities, with the emission wavelength correlating with the degree of aggregation. The absence of photoluminescence in aggregations devoid of ligands underscores the critical role of ligands in the photoluminescence genesis of S-QDs.

Investigation of the aggregation behavior of rubber asphalt components induced by short-term Aging: A perspective from molecular dynamic simulations and microscopic tests

The distribution characteristics of different rubber asphalt components remain a subject of debate, particularly under the influence of asphalt short-term aging. This paper leverages the visualization advantages of molecular dynamics (MD) simulation and integrates them with microscopic testing methods to observe morphological variations and property changes in the aggregation of different components induced by short-term aging. Short-term aging of rubber asphalt is simulated using a thin-film oven test (TFOT). By conducting Fluorescence microscope (FM) and scanning electron microscope (SEM) tests, the aggregation behavior of components under changes in fluorescence phase and microstructure before and after short-term aging is revealed. MD simulation is employed to analyze the degree of aggregation between different components before and after short-term aging. SEM test results indicate that the structure becomes looser and forms distinct pits as the rubber asphalt ages. FM test results reveal that the particle size of rubber powder particles in aged rubber asphalt decreases and aggregates gradually. Concurrently, the asphalt phase in rubber asphalt becomes more uniform after aging. MD simulation results demonstrate significant aggregation between asphaltene-asphaltene molecules and asphaltene-rubber powder molecules in aged rubber asphalt. A higher degree of asphaltene aggregation leads to reduce asphalt penetration and increase softening point and viscosity. Furthermore, rubber powder molecular chains can inhibit “π-π stacking,” and “offset π-π stacking” of the asphaltene molecules. Therefore, the accumulation effect in aged rubber asphalt is mitigated compared with aged base asphalt. The research outcomes provided a foundation for further studies on the aging and rejuvenation of rubber asphalt.

Diffusion in Polymethylene Chain Solutions with a Polar Component.

A hydrodynamic bead model based on Kirkwood-Riseman theory has been used to calculate the translational diffusion constant, D, for solutes with polymethylene chains in solutions with a polar component. A comparison with the experimental values for nonpolar n-alkanes in polar 2-propanol, tetrahydrofuran, chlorobenzene, chloroform, 1-octanol, quinoline, and chloroform (78 D values) and polar primary alcohols in nonpolar benzene and n-octane (24 D values) gives an average absolute percentage difference of ∼3% between the 102 experimental and calculated D values. Consideration of the solvent's temperature-dependent changes in the degree of aggregation due to hydrogen bonding was necessary for the n-alkanes in 1-octanol. Good agreement was not found for primary alcohols in 1-octanol due to solute-solvent hydrogen bonding. A correlation that depends on the solutes' molar volumes instead of their chain lengths gives worse agreement than the bead model for the n-alkanes in polar solvents and primary alcohols and n-alkanes in nonpolar solvents.

In situ continuous hydrogen-bonded engineering for intrinsically stretchable and healable high-mobility polymer semiconductors.

As a key component for wearable electronics, intrinsically stretchable and healable semiconducting polymers are scarce because carrier mobility is often reduced with increasing stretchability and self-healability. Here, we combine stepwise polymerization and thermal conversion to introduce in situ continuous hydrogen bonding sites in a polymer backbone without breaking the conjugation or introducing bulky softer side chains, benefiting the intrachain and interchain charge transport. We demonstrate that a regular sequence structure facilitated the formation of big nanofibers with a high degree of aggregation, providing the loose and porous thin film with simultaneously improved charge transport, stretchability, and self-healability. The mobility of damaged devices can be recovered to 81% after a healing treatment. Fully stretchable transistor based on the designed polymer exhibited a greatly enhanced mobility up to 1.08 square centimeters per volt per second under 100% strain, which is an unprecedented value and constitutes a major step for the development of intrinsically stretchable and healable semiconducting polymers.

Corrosion mechanism of alkali-activated slag/metakaolin materials under carbonic acid solution

For promoting the application of alkali-activated slag/metakaolin (AASM) materials in karst areas, it is crucial to understand the corrosion properties of AASM materials in carbonic acid solutions. This paper systematically investigates the evolution of mechanical properties, phase composition, and microstructure of AASM materials in carbonic acid solution environments. The research results indicate that the corrosion mechanism of AASM in carbonic acid solution environments can be summarized as four stages: the dissolution stage, the C-(N)-A-S-H gel decalcification and calcium carbonate formation stage, the further corrosion of calcium carbonate stage, and the slow corrosion stage. Depending on the degree of Ca2+ leaching, the corrosion layers can be divided from the outermost to the innermost layers into the gel layer, the carbonation layer, and the un-corrosion layer. In carbonic acid solution environments, significant leaching of Na+ and OH− occurs in pore solution, which hinders the development of strength. Additionally, the diffusion of CO32− and HCO3− ions dissolved in water into the C-(N)-A-S-H gel, which react with the gel to form calcium carbonate, leads to gel decomposition. Moreover, the generated calcium carbonate is further corrosion into soluble calcium bicarbonate, resulting in substantial leaching of Ca2+, deterioration of pore structure, and increased aggregation degree of C-(N)-A-S-H gel structure. As the MK content increases, the calcium content in the system decreases, leading to a higher crosslinking degree and enhanced resistance of the C-(N)-A-S-H gel to carbonic acid solution corrosion, thereby reducing the corrosion rate of AASM materials. The research results provide new insights into the application of AASM materials in karst areas.

Evaluating the Effectiveness of Transfer Learning for Predicting the Risk of Autosomal Recessive Diseases Using Pre-Trained Deep Learning Models.

Given the large degree of genetic variability and complicated aggregation, the order of autosomal recessive ataxias faces a significant challenge. As new innovations are developing for extended targeted quality testing, we conducted a thorough intentional review of the literature to look at all recessive ataxias in order to suggest another grouping and suitably embrace this field. The most well-known autosomal recessive genetic disease in the Caucasian population is cystic fibrosis. Expanding knowledge about sub-atomic pathology from one angle enables better description of the changes in CFTR quality and from another viewpoint builds the persuasive force of atomic testing. Accurately predicting endurance in cystic fibrosis (CF) patients can help determine the optimal timing for lung transplantation (LT) in patients with end-stage respiratory disease. Current recommendations state that if the restricted expiratory volume (FEV1) is less than 30% of theoretical, the patient should undergo her LT test. Although FEV1 certainly plays a role in CF-related death, we expected endurance behavior in CF patients to show significantly more variability. Since it is automated, clinical practitioners might very well use it to build prognostic models without needing a deep understanding of machine learning. Our studies showed that the model developed using Auto Prognosis is more accurate than existing rules and other competing models.

Unbiased temperature-related mortality estimates using weekly and monthly health data: a new method for environmental epidemiology and climate impact studies

Exposure to environmental factors has a high burden on human health, with millions of premature annual deaths associated with the short-term health effects of ambient temperatures and air pollution. However, direct estimations of exposure-related mortality from real data are still not available in most parts of the world, especially in low-resource settings, due to the unavailability of daily health records to calibrate epidemiological models. In this study, we have filled the crucial gap in available direct estimations by developing a method to make valid inference for the relationship between exposure and response data that uses only exposure and temporally aggregated response data. We provided the mathematical derivation of the method, and compared the results by using simulations applied to daily temperature and daily, weekly, and monthly mortality data. The method was then applied to the newly created database of the EARLY-ADAPT project. The daily and weekly models produced similar and unbiased estimates of the temperature-related relative risks and attributable mortality, with only slightly more imprecision in the weekly model. Even the estimates of the monthly model were unbiased when using enough data, although at the expense of a substantial increase in variability. The real data analysis showed that the similarity between the regional values of two aggregation models increased with the number of years and regions of the dataset, and decreased with the difference in their degree of temporal aggregation. Our method opens the door to conducting epidemiological studies in low-resource settings, where access to daily health data is not possible. Moreover, it allows accurate estimation of the short-term health effects of environmental exposures in near-real time, when daily health data are still not available, such as in the estimation of the mortality burden of recent record-breaking heat episodes. Overall, our method represents an important new approach to how the public health community can use data to create new evidence for research, translation and policy making. European Research Council (ERC).

Regulation of Reactive Oxygen Species on Platelet Activation and Apoptosis

To investigate how reactive oxygen species (ROS) regulates the signal transduction of platelet activation and apoptosis, and to explore the relationship between platelet activation and apoptosis. Platelets were directly stimulated with thrombin or pretreated with ROS inhibitor N-acetylcysteine (NAC) before being stimulated with thrombin, and then flow cytometry was used to detect the effects of thrombin and NAC on P-selectin expression, αⅡbβ3 activation, mitochondrial membrane potential depolarization, phosphatidylserine (PS) externalization, ROS expression and platelet aggregation. Thrombin could induce the production of ROS in platelets in a concentration- and time-dependent manner. 0.01 U thrombin induced ROS-dependent high degree of integrin αⅡbβ3 activation, P-selectin expression, and platelet aggregation. The platelets induced by different concentration gradients of thrombin exhibited ROS-dependent mitochondrial membrane potential depolarization and PS externalization in platelets. After induction with thrombin for 30 min, the activation of integrin αⅡbβ3 in platelets reached its maximum level, and after 60 minutes, the depolarization of mitochondrial membrane potential in platelets reached its maximum level. However, the expression of P-selectin, depolarization of mitochondrial membrane potential, and platelet aggregation function were all inhibited to a certain extent when the platelets were pretreated with ROS inhibitor NAC and then induced with thrombin. When platelets are induced by thrombin, ROS first regulates the activation of platelets, and then regulates the apoptosis of platelets. Both platelet activation and apoptosis depend on the production of ROS in platelets, and the signals of activation and apoptosis occur orderly. Inhibiting the ROS signal in platelets can effectively inhibit the activation and apoptosis of platelets.

Study in Gas-Phase Agglomeration Characteristics of Spiral Flow Gas-Liquid Multiphase Pump

Abstract The spiral flow gas-liquid mixed transport pump experiences gas phase accumulation in the impeller flow passage, leading to blockage and a decrease in pumping performance. To understand the rules and mechanisms of gas phase aggregation in the spiral flow gas-liquid mixed transport pump, numerical calculations based on the Eulerian multiphase flow model and SST k – ω turbulent flow model were conducted. The effects of different gas volume fractions, speeds, and liquid phase viscosities on the pump were explored, and the external characteristics, flow characteristics, and gas phase aggregation processes in the impeller were analysed for these three variables. The results indicate that the head and efficiency of the pump gradually decrease with increasing gas volume fraction and liquid phase viscosity, while they increase with increasing speed. When the liquid phase viscosity changes from pure water to 50 times its viscosity, the gas phase aggregation at the impeller outlet decreases, resulting in reduced pressure and a smaller vortex region. The relative gas phase aggregation degree λ decreases from 0.5 to almost 0. When the gas volume fraction increases from 20% to 60%, the gas phase aggregation at the impeller outlet increases, the pressure difference between the impeller hub and the rim increases, and the vortex region expands, leading to an increase in λ by 8 times. When the speed increases from 3000 rpm to 5000 rpm, the gas phase aggregation at the impeller outlet increases, the pressure increases, and the vortex region expands, resulting in a 16-fold increase in λ.

Aqueous dispersions of ‘green’ silver nanoparticles for eco-applications: Synthesis, structure and biosafety

Sustainable agriculture requires the use of intelligent compounds with multifaceted effect on soil and plants. Such conditioners can be hydrogels enriched with nanoparticles, but only those synthesized using ‘green chemistry’ methods. Therefore, the main aim of the study was to synthesize and characterize innovative ‘green’ silver nanoparticles (AgNPs) for agricultural applications. AgNPs were created using water or alcohol extracts of eucalyptus (Eucalyptus viminalisLabill) and aloe (Aloë arborescens Mill) as well as tannin to reduce silver ions (Ag+) to zero valent form (Ag0). The synthesis was conducted under autoclave conditions or at room temperature, in the presence of potassium carbonate. The AgNPs characterization was performed by X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM) and dynamic light scattering (DLS) method, whereas stability of the AgNPs suspensions under various conditions was estimated using turbidimetry. Biosafety of the formed species was determined based on genotoxicity (comet test) and cytotoxicity (study with crystal violet and MTT) assays. The obtained results confirmed the presence of zero valent silver phase in the nanoparticles and showed that their crystallite size was 14–24 nm, with different degrees of polydispersity depending on the synthesis conditions. Hydrodynamic diameter of AgNPs and their aggregates in the aqueous dispersions varied from 6 nm to 103 nm, and the smallest aggregation degree was noted for the nanoparticles synthesized using tannin. All synthesized nanoparticles were biosafe. Thus, they can be applied in agro-industrial processes without damaging the environment.