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The influence of core properties on the state of residual oil in the process of oil displacement by water at the micro level is investigated. The pore size distribution, core permeability, dynamics and morphology of residual oil were studied. The analysis of the available experimental approaches to the study of the properties of the core and residual oil in the core samples showed that the existing methods do not provide complete information about the studied parameters. To solve these problems, it is proposed to use a combination of innovative relaxation-diffusion spectroscopy technology of nuclear magnetic resonance with traditional technology. A combination of mercury injection and nuclear magnetic resonance is used to measure the pore size distribution. The core permeability was determined using the nuclear magnetic resonance method. Two-dimensional nuclear magnetic resonance spectroscopy makes it possible to study the microscopic state of residual oil in an undisturbed core during the displacement process. With the help of the proposed methodology, a core study of the Shengli deposit in China was carried out. Pore size distributions were obtained, permeability and residual oil saturation at different stages of displacement were studied. Four types of residual oil are distinguished: strip-shaped (island), film, mesh, continuous. The influence of permeability on the fraction content of different types of residual oil in the process of displacement is shown. The research results demonstrate the influence of the pore space structure and wettability on the state of residual oil.

Silver selenide (Ag2Se) flexible films are promising near‐room‐temperature thermoelectric candidates for low‐grade heat harvesting. However, existing Ag2Se films are generally attached on substrates, which impedes further flexibility improvement of the films and constrains the scenarios of applications. Here a cost‐effective and scalable strategy is presented, which combines screen printing and annealing, for synthesizing freestanding Ag2Se inorganic films with different densities of pores. High‐density pores and thin thickness endow the films with high flexibility, while films with low‐density pores obtain higher power factor. Furthermore, by utilizing the porous microstructure, a composite structure consisting of a Ag2Se conductive network and an organic polydimethylsiloxane (PDMS) skeleton is fabricated, which further improves films’ stability under bending and torsion. Finally, a flexible thermoelectric generator comprising five Ag2Se/PDMS legs and encapsulated PDMS outputs a voltage of 20.2 mV and a maximum power of 810 nW (the corresponding power density is 5.4 W m−2) at a temperature difference of 30 K, verifying potential application at near room temperature. This work offers a useful paradigm for fabricating substrate‐free Ag2Se porous films with high flexibility for near‐room‐temperature thermoelectric applications. [ABSTRACT FROM AUTHOR]

Facial expression recognition(FER) is a hot topic in computer vision, especially as deep learning based methods are gaining traction in this field. However, traditional convolutional neural networks (CNN) ignore the relative position relationship of key facial features (mouth, eyebrows, eyes, etc.) due to changes of facial expressions in real-world environments such as rotation, displacement or partial occlusion. In addition, most of the works in the literature do not take visual tempos into account when recognizing facial expressions that possess higher similarities. To address these issues, we propose a visual tempos 3D-CapsNet framework(VT-3DCapsNet). First, we propose 3D-CapsNet model for emotion recognition, in which we introduced improved 3D-ResNet architecture that integrated with AU-perceived attention module to enhance the ability of feature representation of capsule network, through expressing deeper hierarchical spatiotemporal features and extracting latent information (position, size, orientation) in key facial areas. Furthermore, we propose the temporal pyramid network(TPN)-based expression recognition module(TPN-ERM), which can learn high-level facial motion features from video frames to model differences in visual tempos, further improving the recognition accuracy of 3D-CapsNet. Extensive experiments are conducted on extended Kohn-Kanada (CK+) database and Acted Facial Expression in Wild (AFEW) database. The results demonstrate competitive performance of our approach compared with other state-of-the-art methods. [ABSTRACT FROM AUTHOR]

The acquisition of high-accuracy reflectance in mid-infrared channels is of great significance for the on-orbit cross-calibration of other bands using the mid-infrared band. However, due to the phenomenon that some sensors have a wide range of wavelengths covered by adjacent channels in the mid-infrared band, the traditional method of estimating the mid-infrared reflectivity assumes that the sea surface reflectivity in different mid-infrared bands is equal, which will lead to a large error during calculation. To solve this problem, this study proposes a nonlinear split-window algorithm involving ocean sun glint data to retrieve reflectivity of FY-3D/MERSI-2 channels 20. The results show that the variation range of sea surface reflectivity of channel 20 in the glint area is 10~25%, the mean value of the reflectivity difference obtained by the nonlinear split-window algorithm is 0.27%, and the RMSE is 0.0066. Among the main influencing factors, the atmospheric conditions have the greatest impact, and the effects of the uncertainties in the water vapor content and aerosol optical thickness on the calculation results are 1.16% and 0.34%, respectively. The initial value limits of the mid-infrared sea surface reflectivity also contribute approximately 0.84%, and their contribution to the uncertainty represents one of the main components. This work shows that the nonlinear split-window algorithm can calculate the infrared sea surface reflectivity with high accuracy and can be used as a reference for in-orbit cross-calibration between different bands. [ABSTRACT FROM AUTHOR]