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Carbon Fiber Reinforced Polymer (CFRP) can be used to reinforce steel structures depending on its high strength and lightweight resistance. To analyze and evaluate the load-carrying capacity of CFRP-reinforced steel structures. This study uses the Finite Element Analysis (FEA) and the experimental tests combined to investigate the influence that the reinforcement patterns and the relevant parameters have on the load-carrying capacity. We made specimens with different reinforcement patterns. Take the steel beam specimen with full reinforcement as an example. Compared with the load-carrying capacity of the steel beam reinforced by two-layer CFRP cloth, that respectively increases by 5.16% and 11.1% when the number of the CFRP cloth increases to four and six, respectively. Based on a specimen set consisting of CFRP-reinforced steel structures under different reinforcement patterns, the random forest algorithm is used to develop an evaluation model for the load carrying. The performance test results show that the MAE (Mean Absolute Error) of the evaluation model can reach 0.12 and the RMSE (Root Mean Square Error) is 0.25, presenting a good prediction accuracy, which lays a solid foundation for the research on the CFRP-based reinforcement technology and process.

Syngas conversion is a useful technology for converting nonpetroleum carbon resources into chemicals such as olefins. Iron- and cobalt-based catalysts, as two major categories, have been extensively studied in Fischer–Tropsch synthesis to olefins (FTO) reactions. Although both iron and cobalt catalysts have shown distinct merits and shortcomings, they are also complementary in their properties and catalytic performances when combined with each other. Herein, Na-modified CoFe bimetallic catalysts were fabricated using a co-precipitation method. It was found that there was a synergistic effect between Co and Fe that promoted a CO dissociation rate and carburization, and an appropriate Co/Fe ratio was conducive to improvements in their catalytic performances. The desired olefins selectivity reached 66.1 C% at a CO conversion of 37.5% for a Co2Fe1 catalyst, while the methane selectivity was only 4.3 C%. In addition, no obvious deactivation was found after nearly 160 h, indicating their potential industrial application.

Due to the excellent properties of PEEK and their widely applications in medical industry, it is necessary to conduct a comparative study into the drilling performance and residual tensile behavior of PEEK plates under varying cutting conditions. In this study, the effects of tool geometry, drilling parameters, and slope angles on the thrust force, tool temperature, hole quality are discussed. The residual tensile behavior of the drilled PEEK plates is elucidated in terms of the full-field strain evolution during tensile testing by the Digital Image Correction system. The results showed that drilling parameter and tool geometry affect significantly cutting forces, tool temperature, and resulting hole quality. The relationship between the machinability and the residual tensile property of PEEK is reported for the first time. Full-field strains during tensile testing are sensitive to the level of drilling-induced damages, which have an impact on the residual tensile property of PEEK components.

Accumulating evidence shows that tRNA-derived fragments are a novel class of functional small non-coding RNA; however, their roles in aortic dissection (AD) are still unknown. In this study, we found that 5′-tiRNA-Cys-GCA was significantly downregulated in human and mouse models of aortic dissection. The abnormal proliferation, migration, and phenotypic transition of vascular smooth muscle cells (VSMCs) played a crucial role in the initiation and progression of aortic dissection, with 5′-tiRNA-Cys-GCA as a potential phenotypic switching regulator, because its overexpression inhibited the proliferation and migration of VSMCs and increased the expression of contractile markers. In addition, we verified that signal transducer and activator of transcription 4 (STAT4) was a direct downstream target of 5′-tiRNA-Cys-GCA. We found that the STAT4 upregulation in oxidized low-density lipoprotein (ox-LDL)-treated VSMCs, which promoted cell proliferation, migration, and phenotypic transformation, was reversed by 5′-tiRNA-Cys-GCA. Furthermore, 5′-tiRNA-Cys-GCA treatment reduced the incidence and prevented the malignant process of angiotensin II- and β-aminopropionitrile-induced AD in mice. In conclusion, our findings reveal that 5′-tiRNA-Cys-GCA is a potential regulator of the AD pathological process via the STAT4 signaling pathway, providing a novel clinical target for the development of future treatment strategies for aortic dissection.

The coupled vibration in the turbine disk-blade system (TDS) is one of the main bottlenecks that hinder the further development of high-performance engines. To analyze the vibration of the TDS, three types of contact conditions, involving bonded, frictionless, or frictional were used to simulate the contact between the turbine disk and the blades. Three finite element analysis (FEA) models of a typical TDS based on the tenon structure were developed. The experimental system was developed and experimental modal analysis (EMA) was performed. According to the comparison between FEA and EMA results, the most accurate model is the frictional contact FEA model. The average error of the frictional contact FEA model is 1.42%, and the root mean square error is 0.75%. The working modes of the TDS at different speeds were calculated using the frictional contact FEA model. Meanwhile, based on the newly developed FEA model, it is found that the weak links in the TDS are the blades. This work can provide a theoretical basis for the TDS structure optimization and promote the development of high-quality aero-engines.

In this paper, a visual navigation method based on binocular vision and a deep learning approach is proposed to solve the navigation problem of the unmanned aerial vehicle autonomous aerial refueling docking process. First, to meet the requirements of high accuracy and high frame rate in aerial refueling tasks, this paper proposes a single-stage lightweight drogue detection model, which greatly increases the inference speed of binocular images by introducing image alignment and depth-separable convolution and improves the feature extraction capability and scale adaptation performance of the model by using an efficient attention mechanism (ECA) and adaptive spatial feature fusion method (ASFF). Second, this paper proposes a novel method for estimating the pose of the drogue by spatial geometric modeling using optical markers, and further improves the accuracy and robustness of the algorithm by using visual reprojection. Moreover, this paper constructs a visual navigation vision simulation and semi-physical simulation experiments for the autonomous aerial refueling task, and the experimental results show the following: (1) the proposed drogue detection model has high accuracy and real-time performance, with a mean average precision (mAP) of 98.23% and a detection speed of 41.11 FPS in the embedded module; (2) the position estimation error of the proposed visual navigation algorithm is less than ±0.1 m, and the attitude estimation error of the pitch and yaw angle is less than ±0.5°; and (3) through comparison experiments with the existing advanced methods, the positioning accuracy of this method is improved by 1.18% compared with the current advanced methods.

Abstract Microbial‐assisted biosynthesis of silver nanoparticles (AgNPs) has been developed rapidly in recent years, but their mechanism of synthesis and production are still unknown. This study investigated the roles of nitrate reductase produced by the fungus Trichoderma asperellum in the synthesis of AgNPs. The nitrate reductase activity is activated by nitrate and showed a positive correlation with the quantity of AgNPs, which may lead to the development of a fast bioprocess of AgNPs synthesis. Treatment of silver nitrate with the fungal supernatant containing nitrate reductase produced stable, monodispersed, and spherical AgNPs with an average size of 20 nm, which were characterized by UV–visible spectroscopy, scanning electron microscopy and X‐ray diffraction. SDS‐PAGE implied that nitrate reductases were involved in the synthesis of AgNPs. The antifungal activities of synthesized AgNPs solution were compared with those of silver nitrate solution and AgNPs‐free supernatant solution. The results showed that AgNPs solution exhibited the highest antifungal activity against several selected plant pathogens by the agar well diffusion method. This study firstly concluded that extracellular biosynthesis of AgNPs could be promoted by potassium nitrate in Trichoderma asperellum Q1 media and the AgNPs provided a potential enhancement of biocontrol activity derived from the fungi.

To develop the intensive breeding technology of the seed of the red swamp crayfish Procambarus clarkii, the survival rates, hatching effects (hatching rate, incubation level, and number of juveniles), and immune performance of ovigerous P. clarkia as well as economic benefits are evaluated under different shelter conditions under a high stocking density in this study. The experimental design includes three different forms of shelter treatments (D1: experiment without any shelters; D2: experiment with closed shelters; D3: experiment with open shelters), each with three replicates. The results show that the concentration of the total antioxidant capacity (T-AOC) and activities of phenoloxidase (PO), catalase (CAT), and acid phosphatase (ACP) in the D3 treatment are higher than those in the D1 treatment (all p < 0.05), with the highest concentrations of total antioxidant capacity (T-AOC) and malondialdehyde (MDA) and the highest activities of phenoloxidase (PO), superoxide dismutase (SOD), catalase (CAT), acid phosphatase (ACP), and alkaline phosphatase (AKP) among the treatments being present in the ovigerous P. clarkii in the D3 treatment. The hatching rates of the three treatments vary from 69.51% to 94.28%, with the highest rate found in the D3 treatment and the lowest in the D1 treatment, but there is no significant difference among them (p > 0.05). The highest incubation level (ind.·m−2) and the highest number of juveniles (ind.·m−2) among treatments are found in the D3 treatment, with the incubation level (ind.·m−2) in the D3 treatment being significantly higher than that in the D1 treatment (p < 0.05). The benefit–cost ratios (BCRs) of the D2 and D3 treatments remain significantly higher than that of the D1 treatment when P. clarkii prices change (all p < 0.05). Our results indicate that a high stocking density habitat with open shelters could effectively improve the hatching and immune performance of ovigerous P. clarkii. Our findings are relevant for the indoor aquaculture management of ovigerous P. clarkii.

The PixelHop framework based on successive subspace learning (SSL) has been widely used in signal processing and computer vision, which can effectively improve the classification accuracy in high spatial resolution scenes through successive subspace growth. To solve the problems of insufficient feature extraction and dependence on prior knowledge in the PixelHop framework, an improved PixelHop (I-PixelHop) framework is proposed. On the basis of PixelHop framework, I-PixelHop has made the following improvements. 1) I-PixelHop fully extracts the continuous features in one-dimensional sequence data through the improved neighborhood expansion, which can provide a richer feature set. 2) The improved label-assisted regression (ILAG) unit uses the Bi-K-Means clustering algorithm to enable more correct clustering of similar samples, and it adopts the cross-entropy threshold method to alleviate the negative effects caused by the improper setting of the number of pseudo-classes. 3) The high-dimensional features are fully reused by adopting the pseudo dense connection structure to obtain a better feature set. Moreover, the proposed I-PixelHop framework is applied to the rolling bearing fault diagnosis. A series of experiments are carried out to verify the effectiveness of the proposed I-PixelHop. The experimental results show that the fault diagnosis accuracy of I-PixelHop can reach 98.91% and 98.74% on the two different rolling bearing fault datasets, and it also has satisfactory anti-noise ability, faster training speed, and smaller model size.

The random forest (RF) algorithm is a typical representative of ensemble learning, which is widely used in rolling bearing fault diagnosis. In order to solve the problems of slower diagnosis speed and repeated voting of traditional RF algorithm in rolling bearing fault diagnosis under the big data environment, an efficient rolling bearing fault diagnosis method based on Spark and improved random forest (IRF) algorithm is proposed. By eliminating the decision trees with low classification accuracy and those prone to repeated voting in the original RF, an improved RF with faster diagnosis speed and higher classification accuracy is constructed. For the massive rolling bearing vibration data, in order to improve the training speed and diagnosis speed of the rolling bearing fault diagnosis model, the IRF algorithm is parallelized on the Spark platform. First, an original RF model is obtained by training multiple decision trees in parallel. Second, the decision trees with low classification accuracy in the original RF model are filtered. Third, all path information of the reserved decision trees is obtained in parallel. Fourth, a decision tree similarity matrix is constructed in parallel to eliminate the decision trees which are prone to repeated voting. Finally, an IRF model which can diagnose rolling bearing faults quickly and effectively is obtained. A series of experiments are carried out to evaluate the effectiveness of the proposed rolling bearing fault diagnosis method based on Spark and IRF algorithm. The results show that the proposed method can not only achieve good fault diagnosis accuracy, but also have fast model training speed and fault diagnosis speed for large-scale rolling bearing datasets.

Ensemble learning has been widely used in various fields. Still, too many base classifiers will affect the classification time of the ensemble classifier under the big data environment, while reducing base classifiers will affect the classification accuracy of the ensemble classifier. Therefore, the multi-objective teaching-learning-based optimization (MO-TLBO) algorithm is used to carry out ensemble pruning of random forest (RF) to improve the classification accuracy and speed of RF. MO-TLBO algorithm aims at maximizing classification accuracy and minimizing classification time, and it can find a sub-forest with higher classification accuracy and faster classification speed. In addition, considering the vast computational time of ensemble pruning of RF via MO-TLBO algorithm under the big data environment, a vote set is constructed to improve the fitness evaluation process. In the Spark platform, the RF improved by the MO-TLBO algorithm (MO-TLBO-RF) is parallelized based on data parallelism. The Shuffle optimization strategy is proposed to reduce the number of Shuffles in the execution of parallel MO-TLBO-RF. The proposed MO-TLBO-RF is applied to rolling bearing fault diagnosis. The experimental results show that the algorithm can obtain an RF with high fault diagnosis accuracy and fast fault diagnosis speed. The results also prove that the ensemble pruning time can be greatly reduced via the vote set and parallelization of MO-TLBO-RF.

The clustering effect of the spectral clustering algorithm depends on the calculation of the similarity between samples. Although a better clustering effect of the spectral clustering algorithm can be obtained using the Gaussian kernel function to calculate the similarity between samples, it relies on the setting of the kernel parameter. Therefore, an adaptive density-sensitive similarity measure based spectral clustering (DSSC) algorithm is proposed for improving the clustering effect. Specifically, firstly, the Euclidean distances between samples are calculated to get the nearest neighbors of each sample. Secondly, the standard deviation of distances between each sample and its nearest neighbors is calculated as the density parameter. Thirdly, the density-sensitive distances between each sample and its nearest neighbors are calculated. Finally, the similarities between each sample and its nearest neighbors are calculated to construct a similarity matrix. In addition, the proposed DSSC algorithm is parallelized on Dask distributed parallel computing platform with CPU+GPU, which can improve the computational efficiency of the DSSC algorithm by taking full advantage of the CPU and GPU resources. A series of experiments are conducted to verify the effectiveness of the proposed DSSC algorithm on several synthetic datasets and UCI datasets, and the results show that the DSSC algorithm not only achieves satisfactory clustering results, but also obtains better efficiency of performing large-scale clustering analysis.

Abstract Background Mitral regurgitation volume (MRvol) by quantitative pulsed Doppler (QPD) method previously recommended suffers from geometric assumption error because of circular geometric assumption of mitral annulus (MA). Therefore, the aim of this study was to evaluate the impact of different geometric assumption of MA on the assessment of MRvol by two-dimensional transthoracic echocardiographic QPD method. Methods This study included 88 patients with varying degrees of mitral regurgitation (MR). The MRvol was evaluated by QPD method using circular or ellipse geometric assumption of MA. MRvol derived from effective regurgitant orifice area by real time three-dimensional echocardiography (RT3DE) multiplied by MR velocity-time integral was used as reference method. Results Assumption of a circular geometry of MA, QPD-MAA4C and QPD-MAPLAX overestimated the MRvol by a mean difference of 10.4 ml (P < 0.0001) and 22.5 ml (P < 0.0001) compared with RT3DE. Assumption of an ellipse geometry of MA, there was no significant difference of MRvol (mean difference = 1.7 ml, P = 0.0844) between the QPD-MAA4C + A2C and the RT3DE. Conclusions Assuming that the MA was circular geometry previously recommended, the MRvol by QPD-MAA4C was overestimated compared with the reference method. However, assuming that the MA was ellipse geometry, the MRvol by the QPD-MAA4C + A2C has no significant difference with the reference method.

Tooth enamel machining is a common procedure in dental surgery, yet the cutting mechanisms and performance of different dental burs remain unclear. In the dental field, this poses challenges for dentists in selecting appropriate dental burs for specific operations. In the engineering field, this creates difficulties in understanding the cutting mechanisms of tooth enamel and designing new high-performance dental burs. Therefore, the objective of this study is to bridge the gap between medicine and engineering by comprehending the cutting mechanisms and performance of different dental burs for tooth enamel machining. This study established an enamel machining experimental system and utilized the fissure bur, diamond bur, and round bur to conduct enamel drilling and milling experiments on the occlusal, buccal/lingual, and mesial/distal surfaces of the tooth. The results indicate that, compared to the buccal/lingual and mesial/distal surfaces, the milling force is lower ( p < 0.05) but the milling temperature is higher ( p < 0.05) on the occlusal surface. Furthermore, the fissure bur generated the lowest drilling and milling temperatures ( p < 0.05) and the best milling quality. The diamond bur generated the best drilling quality but lacked drilling precision ( p < 0.05). The round bur generated the smallest drilling force ( p < 0.05) but the largest milling force ( p < 0.05). The analysis of the structure and cutting mechanisms of different dental burs on various tooth surfaces explains the aforementioned phenomena. Different dental burs have distinct advantages based on their structures. This study enhances the understanding of tooth enamel cutting mechanisms and dental bur machining performance in the field of medicine and engineering, which can improve the quality of dental surgery and facilitate the development of high-performance dental burs.

Abstract Background and Objectives This study aimed to assess the changes of RA function in patients with obstructive sleep apnea syndrome (OSAS) using velocity vector imaging (VVI) and to evaluate the application of VVI technology. Methods According to the apnea–hypopnea index (AHI), 71 patients with OSAS were divided into three groups: mild, moderate, and severe. A total of 30 cases of healthy subjects were enrolled as the control group. Digital images of apex four-chamber views were acquired to measure the right atrium (RA) linear dimensions and volume parameters including RA longitudinal diameter (RAL), transverse diameter (RAT), RA maximum volume (Vmax), RA minimum volume (Vmin), right atrial volume before contraction (Vpre). Right atrial volume parameters were corrected by body surface area (VImax, VImin, VIpre). The total right atrial emptying fraction (RATEF), right atrial passive emptying fraction (RAPEF), right atrial active contraction emptying fraction (RAAEF) were calculated. The VVI data measuring right atrial global strain (RA-GLS), right atrial strain rate in ventricular systolic phase (RA-SRs), right atrial strain rate in ventricular early diastolic phase (RA-SRe), right atrial strain rate in ventricular late diastolic phase (RA-SRa). Results 1.RA linear dimensions and volume parameters in severe OSAS were higher than those of control group. RAPEF in severe group was lower than control group and mild OSAS group (t = 2.681, P = 0.021; t = 2.985, P = 0.011; respectively). RAAEF in OSAS moderate group was higher than that of control group (t = 3.006, P = 0.02), and without statistical difference (P > 0.05) in the severe OSAS group and the control group.2.RA-GLS in moderate OSAS group was significantly lower than that of control group (t = 2.333, P = 0.040) and reduced more obvious in the severe OSAS group (vs control, t = 3.25, P = 0.008, vs mild; t = 3.011, P = 0.012; respectively). RA-SRe in moderate and severe OSAS groups were lower than control group (t = 2.466, P = 0.031; t = 3.547, P = 0.005; respectively). RA-SRs of OSAS in severe group was lower than that of control and mild groups (t = 3.665, P = 0.004; t = 3.204, P = 0.008; respectively). RA-SRa in severe OSAS group was lower than that of control group (t = 2.425, P = 0.034).3.Multivariate regression analysis showed that RA-GLS and RA-SRe were independently correlated with AHI (t = − 2.738, P = 0.010; t = − 2.191, P = 0.036; respectively). Conclusion RA function was impaired in patients with OSAS. On hemodynamics, the change of RA function performed increased of reserve function, reduced pipeline function and increased of contraction function. However, the strain and strain rate reduced in different degree. RA-GLS and RA-SRe decreased the earliest, which suggested that strain and strain rate were the parameters which can reflect myocardial function damage earliest. VVI can more earlier and accurately detect myocardial dysfunction of right atrium in patients with OSAS, which is expected to be a worthy technique for early clinical therapy in patients with OSAS.

Abstract Background The myocardial wall of the left ventricle is a complex, multilayered structure and is not homogenous. The aim of this study was to determine longitudinal strain (LS) in the three myocardial layers in normal pregnant women according to gestation proceedings. Methods The advanced two-dimensional speckle tracking echocardiography (2D STE) was performed on 62 women during each pregnancy trimester and 6 to 9 weeks after delivery, while 30 age-matched, healthy, nonpregnant women served as controls. LS on endocardial, mid-myocardial and epicardial layers at 18 cardiac segments were measured. Results As gestation proceeded, all of layer-specific LS and global LS progressively decreased, which subsequently recovered postpartum (P

Objective A patent foramen ovale (PFO) is detected frequently by echocardiography. However, a thrombus trapped in a PFO is relatively rare. We herein describe a rare case of a 51-year-old patient with pulmonary embolism in which a large thrombus-in-transit through a PFO was found by echocardiography and disappeared after treatment. Methods A 51-year-old woman presented with a 1-week history of chest tightness, unspecified chest pain, and shortness of breath. Echocardiography revealed a large thrombus trapped in a PFO with increased pulmonary artery pressure, which is a very rare and critical condition. Results The patient was treated with thrombolysis and anticoagulation and discharged from the hospital with an uneventful recovery. Conclusion Our treatment of the present patient achieved a satisfactory result, but it may not be applicable to every patient. Echocardiography is a readily available and safe tool for demonstrating the size, location, and extent of a thrombus, and it plays an important role in the early diagnosis and treatment evaluation for patients with a thrombus trapped in a PFO with concurrent pulmonary embolism.

Cell transplantation has emerged as a novel therapeutic strategy for periodontitis, and the adoption of cell pellet offers advantages by secreting abundant extracellular matrix (ECM) and eliminating the adverse effect of cell carriers. This study aimed to fabricate scaffold-free periodontal ligament stem cell (PDLSC) pellets (MUCPs) and to evaluate their regeneration potential. We constructed monolayer cell pellets (MCPs) by fabricating and culturing multilayered cell sheets (MUCS) and constructed MUCPs from the MUCS. Immunochemistry, scanning electron microscope, real-time PCR, and Western blot analysis showed higher levels of COL-I, COL-III, fibronectin, and laminin in the MUCPs. Furthermore, the massive increase in ECM secretion improved cell adhesion, migration, and proliferation. Finally, upon transplantation into the omentum sac and periodon-tal defects, all the transplants formed regular aligned cementum/PDL-like complex, but the mineral deposit and fiber alignment were more obvious in the MUCPs than in the MCPs. Altogether, our results suggest that MUCPs may be a promising alternative to periodontal repair for future clinical application.

The α2-adrenoceptor agonist dexmedetomidine is a commonly used drug for sedatives in clinics and has analgesic effects; however, its mechanism of analgesia in the spine remains unclear. In this study, we systematically used behavioural and transcriptomic sequencing, pharmacological intervention, electrophysiological recording and ultrasound imaging to explore the analgesic effects of the α2-adrenoceptor and its molecular mechanism. Firstly, we found that spinal nerve injury changed the spinal transcriptome expression, and the differential genes were mainly related to calcium signalling and tissue metabolic pathways. In addition, α2-adrenoceptor mRNA expression was significantly upregulated, and α2-adrenoceptor was significantly colocalised with markers, particularly neuronal markers. Intrathecal dexmedetomidine suppressed neuropathic pain and acute inflammatory pain in a dose-dependent manner. The transcriptome results demonstrated that the analgesic effect of dexmedetomidine may be related to the modulation of neuronal metabolism. Weighted gene correlation network analysis indicated that turquoise, brown, yellow and grey modules were the most correlated with dexmedetomidine-induced analgesic effects. Bioinformatics also annotated the involvement of metabolic processes and neural plasticity. A cardiovascular--mitochondrial interaction was found, and ultrasound imaging revealed that injection of dexmedetomidine significantly enhanced spinal cord perfusion in rats with neuropathic pain, which might be regulated by pyruvate dehydrogenase kinase 4 (pdk4), cholesterol 25-hydroxylase (ch25 h) and GTP cyclohydrolase 1 (gch1). Increasing the perfusion doses of dexmedetomidine significantly suppressed the frequency and amplitude of spinal nerve ligation-induced miniature excitatory postsynaptic currents. Overall, dexmedetomidine exerts analgesic effects by restoring neuronal metabolic processes through agonism of the α2-adrenoceptor and subsequently inhibiting changes in synaptic plasticity. [ABSTRACT FROM AUTHOR]

Foam is utilized in enhanced oil recovery and CO2 sequestration. Surfactant-alternating-gas (SAG) is a preferred approach for placing foam into reservoirs, due to it enhances gas injection and minimizes corrosion in facilities. Our previous studies with similar permeability cores show that during SAG injection, several banks occupy the area near the well where fluid exhibits distinct behaviour. However, underground reservoirs are heterogeneous, often layered. It is crucial to understand the effect of permeability on fluid behaviour and injectivity in a SAG process. In this work, coreflood experiments are conducted in cores with permeabilities ranging from 16 to 2300 mD. We observe the same sequence of banks in cores with different permeabilities. However, the speed at which banks propagate and their overall mobility can vary depending on permeability. At higher permeabilities, the gas-dissolution bank and the forced-imbibition bank progress more rapidly during liquid injection. The total mobilities of both banks decrease with permeability. By utilizing a bank-propagation model, we scale up our experimental findings and compare them to results obtained using the Peaceman equation. Our findings reveal that the liquid injectivity in a SAG foam process is misestimated by conventional simulators based on the Peaceman equation. The lower the formation permeability, the greater the error. [ABSTRACT FROM AUTHOR]