A network structure (DRSN-GAN) is proposed for image motion deblurring that combines a deep residual shrinkage network (DRSN) with a generative adversarial network (GAN) to address the issues of poor noise immunity and low generalizability in deblurring algorithms based solely on GANs. First, an end-to-end approach is used to recover a clear image from a blurred image, without the need to estimate a blurring kernel. Next, a DRSN is used as the generator in a GAN to remove noise from the input image while learning residuals to improve robustness. The BN and ReLU layers in the DRSN were moved to the front of the convolution layer, making the network easier to train. Finally, deblurring performance was verified using the GoPro, Köhler, and Lai datasets. Experimental results showed that deblurred images were produced with more subjective visual effects and a higher objective evaluation, compared with algorithms such as MPRNet. Furthermore, image edge and texture restoration effects were improved along with image quality. Our model produced slightly higher PSNR and SSIM values than the latest MPRNet, as well as increased YOLO detection accuracy. The number of required parameters in the DRSN-GAN was also reduced by 21.89%.
An optimal second-order integral sliding mode control (OSISMC) strategy is proposed for the stabilization control of underactuated robotic system. The proposed control strategy consists of an optimal control law and a second-order integral sliding mode (SISM) control law. The optimal control law is designed for the nominal system by the state-dependent Riccati equation (SDRE), making the system reach the optimal performance. Then, the optimal control law is introduced into the integral sliding mode surface, ensuring the robustness to the disturbance. In order to weaken the chattering, a SISM sliding surface is further designed and the OSISMC is obtained. The stabilization of the system is proved by Lyapunov theory. The simulation shows that the proposed OSISMC can improve the control performance and reduce the chattering.
The effects of chain topology on the self-assembly of block copolymers are examined using an ABAT block copolymer, composed of an AB diblock copolymer with an extra A block tethered onto the B block, as a model system. The topology of the ABAT block copolymer is regulated by the tethering point, such that the block copolymer changes continuously from linear ABA triblock copolymer to A2B miktoarm star copolymer as the tethering position moves from the B end to the AB junction. The phase diagrams of ABAT copolymers of different tethering positions are constructed using the self-consistent field theory. The theoretical results reveal that the phase behavior of the system depends sensitively on the topology of the ABAT copolymers. In particular, a considerably wide stable region of the perforated lamellar (PL) phase is predicted for ABAT with proper tethering positions. The PL phase could even completely replaces the gyroid phase at relatively strong segregation. Furthermore, a large window of the hexagonally close-packed (hcp) spherical phase, as well as a direct transition from hcp to the cylindrical phase, is predicted. An analysis of the distributions of the different blocks reveals that the local segregation of the two different B blocks occurs to accommodate the topological constraints due to the chain architecture, which in turn regulates the local interfacial curvature and chain packing resulting in the different phase behaviors.
Spectral induced polarization (SIP) has been used in east China for nearly 20 years to evaluate hydrocarbon charge. In assessing 65 wells in six oil fields in east China, SIP made 47 successful positive (producer) and negative (dry hole) predictions for a success rate of 72.3%.
Conventional optical microscopes are only able to resolve objects down to a size of approximately 200 nm due to optical diffraction limits. The rapid development of nanotechnology has increased the demand for greater imaging resolution, with a need to break through those diffraction limits. Among super-resolution techniques, microsphere imaging has emerged as a strong contender, offering low cost, simple operation, and high resolution, especially in the fields of nanodevices, biomedicine, and semiconductors. However, this technology is still in its infancy, with an inadequate understanding of the underlying principles and the technology’s limited field of view. This paper comprehensively summarizes the status of current research, the advantages and disadvantages of the basic principles and methods of microsphere imaging, the materials and preparation processes, microsphere manipulation methods, and applications. The paper also summarizes future development trends.
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