Numerical simulations on compression behaviors of the laminated shale based on the digital image technology and the discrete element method.

As an unconventional reservoir sedimentary rock, shale contains a series of layers and various microstructures that lead to complex mechanical properties, such as the anisotropy of stiffness and strength. This study is directed towards the anisotropy caused by the microstructures of the shale, employing the 2D particle flow code (PFC2D) to explore stiffness, strength, failure mode, and micro-crack evolution. More realistic microstructures and the calibration of microscopic parameters of the shale are reasonably considered through the computed tomography (CT) images and mineral analysis. The corresponding numerical simulation results are fully compared with the experimental results. In what follows, the sensitivity analysis is conducted on the key microscopic parameters and microstructure characteristics in numerical samples with laminated characteristics. The results show that the influence of microscopic parameters of the parallel bonding model on macroscopic parameters is related to the layering angle and the face type, and the microstructures and initial cracks of numerical samples can considerably affect the macroscopic mechanical behaviors of the laminated samples. Next, the effect of confining pressure on the mechanical properties of layered shale is also discussed based on the numerical results. These findings highlight the potential of this approach for applications in micro-scaled models and calibration of microscopic parameters to probe mechanical behaviors of the laminated rock.

Axisymmetric Compression of a Circular Particle Raft Driven by the Diffusion of Surfactant.

Particle rafts are a new kind of soft matter formed by self-organization on the interface, which possesses mechanical properties between fluid and solid, and they have been widely used in many industrial fields. In the present study, the compression experiment of a circular particle raft is first performed, where an SDS (sodium dodecyl sulfate)-coated metal ring is placed around its periphery. When the surfactant diffuses, the particle raft shrinks, and its shrinkage ratio increases with the increase in the surfactant concentration, where the experimental results are consistent with the numerical simulation. Next, the relationship between the initial surface tension difference of SDS and the radius shrinkage of the particle raft is obtained by dimensional analysis. In what follows, the diffusion model is built to quantify the diffusion process of SDS at the liquid-gas interface, and then the analytical concentration solution of the concentration of SDS at the periphery of particle raft is given. The particle raft is viewed as an elastic circular plate under the action of the radial pressure, which originates from the surface tension difference, which has been verified by the experimental result. These explorations cast a new light on how to apply loads to measure mechanical properties of soft matter, which also provide some inspirations on the design of microsensors and microfluidics.

ROP-GAN: an image synthesis method for retinopathy of prematurity based on generative adversarial network.

Objective. Training data with annotations are scarce in the intelligent diagnosis of retinopathy of prematurity (ROP), and existing typical data augmentation methods cannot generate data with a high degree of diversity. In order to increase the sample size and the generalization ability of the classification model, we propose a method called ROP-GAN for image synthesis of ROP based on a generative adversarial network.Approach. To generate a binary vascular network from color fundus images, we first design an image segmentation model based on U2-Net that can extract multi-scale features without reducing the resolution of the feature map. The vascular network is then fed into an adversarial autoencoder for reconstruction, which increases the diversity of the vascular network diagram. Then, we design an ROP image synthesis algorithm based on a generative adversarial network, in which paired color fundus images and binarized vascular networks are input into the image generation model to train the generator and discriminator, and attention mechanism modules are added to the generator to improve its detail synthesis ability.Main results. Qualitative and quantitative evaluation indicators are applied to evaluate the proposed method, and experiments demonstrate that the proposed method is superior to the existing ROP image synthesis methods, as it can synthesize realistic ROP fundus images.Significance. Our method effectively alleviates the problem of data imbalance in ROP intelligent diagnosis, contributes to the implementation of ROP staging tasks, and lays the foundation for further research. In addition to classification tasks, our synthesized images can facilitate tasks that require large amounts of medical data, such as detecting lesions and segmenting medical images.

Ion-Specific Effects on Vesicle-to-Micelle Transitions of an Amino Acid Surfactant Probed by Chemical Trapping.

Ion-specific effects widely exist in biological and chemical systems and cannot be explained by classical theories. The complexity of ion-specific effects in protein systems at the molecular level necessitates the use of mimetic models involving smaller molecules, such as amino acids, oligopeptides, and other organic molecules bearing amide bonds. Therefore, it is of theoretical value to determine the effect of additional salts on the aggregation transitions of acyl amino acid surfactants. Herein, the effects of specific tetraalkylammonium ions (TAA+) on sodium lauroyl glycinate (SLG) aggregation were studied by dynamic light scattering (DLS) and transmission electron microscopy. Although previous studies have shown that the kosmotropic TAA+ ions tend to induce micellar growth or micelle-to-vesicle transitions of some anionic surfactants, TAA+ addition in the present study induced partial vesicle-to-micelle transitions in SLG solutions. The chemical trapping (CT) method was employed to estimate changes in the interfacial molarities of water, amide bonds, and carboxylate groups during such transitions. The vesicle-to-micelle transitions were accompanied by a marked rise in interfacial water molarity and a decline in interfacial amide bonds molarity, suggesting that the hydrated TAA+ entered the interfacial region and disrupted hydrogen bonding, thus preventing the SLG monomers from packing tightly. Molecular dynamic simulation was also performed to demonstrate the salt-induced cleavage of amide-amide bonds between SLG headgroups. Furthermore, both CT and DLS results show that the ability of tetraalkylammonium cations to induce such transitions increased with increasing size and hydrophobicity of the cation, which follows the Hofmeister series. The current study offers critical molecular-level evidence for understanding the specific effects of tetraalkylammonium ions on the aggregation transitions of an acyl amino acid surfactant.

A Deep-Learning-Based Collaborative Edge-Cloud Telemedicine System for Retinopathy of Prematurity.

Retinopathy of prematurity is an ophthalmic disease with a very high blindness rate. With its increasing incidence year by year, its timely diagnosis and treatment are of great significance. Due to the lack of timely and effective fundus screening for premature infants in remote areas, leading to an aggravation of the disease and even blindness, in this paper, a deep learning-based collaborative edge-cloud telemedicine system is proposed to mitigate this issue. In the proposed system, deep learning algorithms are mainly used for classification of processed images. Our algorithm is based on ResNet101 and uses undersampling and resampling to improve the data imbalance problem in the field of medical image processing. Artificial intelligence algorithms are combined with a collaborative edge-cloud architecture to implement a comprehensive telemedicine system to realize timely screening and diagnosis of retinopathy of prematurity in remote areas with shortages or a complete lack of expert medical staff. Finally, the algorithm is successfully embedded in a mobile terminal device and deployed through the support of a core hospital of Guangdong Province. The results show that we achieved 75% ACC and 60% AUC. This research is of great significance for the development of telemedicine systems and aims to mitigate the lack of medical resources and their uneven distribution in rural areas.

Simultaneous determination of interfacial molarities of an alcohol, bromide ion, and water during an alcohol induced microstructural transition: the difference between medium and long chain alcohols.

The transitions between surfactant aggregate structures are triggered by changes in chemical or physical stimulations, including addition of additives. Effects of added alcohols on aggregate morphologies correlate strongly with alcohol chain length. The local molarities of alcohol, water, and counterions in the interfacial regions play an important role in controlling the aggregate morphologies. However, direct experimental estimates of changes of interfacial alcohol molarities during alcohol induced micelle-to-vesicle transitions have never been reported. Ellipsoidal-wormlike micelle-vesicle transitions in CTAB/KBr aqueous solutions in the presence of long-chain octanol were characterized by using combined rheological, dynamic light scattering (DLS), transmission electron microscopy (TEM) and turbidity measurements. However, the transitions are absent with added butanol. The chemical trapping method (CT) was employed to understand the differences between medium- and long-chain alcohols in determining aggregate morphology. The CT method was used to estimate interfacial water, alcohol, and counterion molarities with increasing stoichiometric alcohol concentrations. With 55 mM alcohol added, the interfacial octanol molarity is 0.9 M, which is three times higher than that for butanol. With added octanol, the ellipsoidal-wormlike micelle-vesicle transition is accompanied by a concurrent sharp increase of interfacial water molarities and a decrease of interfacial counterion molarity, which is not observed with added butanol. The CT data was also employed to estimate the changes of Israelachvili's packing parameter with increasing added alcohol concentration. Our result provides critical molecular level information for understanding the morphological transitions of CTAB/additives.

Effect of ß-endoxylanase and α-arabinofuranosidase enzymatic hydrolysis on nutritional and technological properties of wheat brans.

Wheat bran (WB) was treated using xylanase and arabinofuranosidase from Thermotoga maritima and added to steamed breads on 15% flour weight basis. The antioxidant capacity and water and oil retention capacity of brans were increased while their soluble xylooligosaccharides and phenolic acids content were increased. Two enzymes treatment was found to be more effective in decreasing the resistance to extension, softening degree, water absorption and development time, and in increasing the extensibility, stability time, porosity and sensorial characteristics of the steamed breads. Two enzymes treatment had significantly (P < 0.05) greater specific volume, springiness and cohesiveness and lower crumb firmness, gumminess, chewiness than single enzyme treatment. All results highlighted that combination of xylanase and arabinofuranosidase can improve the degrees hydrolysis of WB and its soluble AX xylooligosaccharides produced, having a synergetic effect on the dough rheology and nutritional and quality characteristics of steamed bread.