Excellent energy storage performance in Bi0.5Na0.5TiO3-based lead-free high-entropy relaxor ferroelectrics via B-site modification

Next-generation advanced high/pulsed power capacitors urgently require dielectric materials with outstanding energy storage performance. Bi0.5Na0.5TiO3-based lead-free materials exhibit high polarization, but the high remanent polarization and large polarization hysteresis limit their applications in dielectric capacitors. Herein, high-entropy perovskite relaxor ferroelectrics (Na0.2Bi0.2Ba0.2Sr0.2Ca0.2)(Ti1−x%Zrx%)O3 are designed by adding multiple ions in the A-site and replacing the B-site Ti4+ with a certain amount of Zr4+. The newly designed system showed high relaxor feature and slim polarization–electric (P–E) loops. Especially, improved relaxor feature and obviously delayed polarization saturation were found with the increasing of Zr4+. Of particular importance is that both high recoverable energy storage density of 6.6 J/cm3 and energy efficiency of 93.5% were achieved under 550 kV/cm for the ceramics of x = 6, accompanying with excellent frequency stability, appreciable thermal stability, and prosperous discharge property. This work not only provides potential dielectric materials for energy storage applications, but also offers an effective strategy to obtain dielectric ceramics with ultrahigh comprehensive energy storage performance to meet the demanding requirements of advanced energy storage applications

A novel Patient-Specific Three-Dimensional Printing Template Based on External Fixation for Pelvic Screw Insertion

Purpose To investigate the clinical effect of novel patient-specific 3D printing templates based on external fixation for pelvic screw insertion compared with the fluoro-navigation technique. Materials and methods We retrospectively studied 18 pelvic fracture patients from July 2017 to July 2018. For analysis, patients were divided into two groups: the template group (15 screws in 8 patients) and the fluoro-navigation group (22 screws in 10 patients). The screw insertion time, radiation exposure time, and accuracy of the screw insertion as evaluated by postoperative CT scans were analyzed. Results In the template group, the average screw insertion time (11.5 ± 2.3 min/screw) was significantly 50.6% less than that in the fluoro-navigation group (23.3 ± 3.1 min/screw; P < 0.05). The average time of X-ray exposure in the template group (11.5 ± 3.9 s/screw) was also significantly 39.8% less than in the fluoro-navigation group (19.1 ± 2.5 s/screw; P < 0.05). In the template group, the mean deviation distance and angle between the actual and planned screw position was 2.6 ± 0.2 mm and 2 ± 0.3°. Conclusions The patient-specific template based on external fixation can guide the insertion of the pelvic screw accurately and safely while significantly reducing operation and radiation exposure time

Sparse Bayes Tensor and DOA Tracking Inspired Channel Estimation for V2X Millimeter Wave Massive MIMO System

Efficient vehicle-to-everything (V2X) communications improve traffic safety, enable autonomous driving, and help to reduce environmental impacts. To achieve these objectives, accurate channel estimation in highly mobile scenarios becomes necessary. However, in the V2X millimeter-wave massive MIMO system, the high mobility of vehicles leads to the rapid time-varying of the wireless channel and results in the existing static channel estimation algorithms no longer applicable. In this paper, we propose a sparse Bayes tensor and DOA tracking inspired channel estimation for V2X millimeter wave massive MIMO system. Specifically, by exploiting the sparse scattering characteristics of the channel, we transform the channel estimation into a sparse recovery problem. In order to reduce the influence of quantization errors, both the receiving and transmitting angle grids should have super-resolution. We obtain the measurement matrix to increase the resolution of the redundant dictionary. Furthermore, we take the low-rank characteristics of the received signals into consideration rather than singly using the traditional sparse prior. Motivated by the sparse Bayes tensor, a direction of arrival (DOA) tracking method is developed to acquire the DOA at the next moment, which equals the sum of the DOA at the previous moment and the offset. The obtained DOA is expected to provide a significant angle information update for tracking fast time-varying vehicular channels. The proposed approach is evaluated over the different speeds of the vehicle scenarios and compared to the other methods. Simulation results validated the theoretical analysis and demonstrate that the proposed solution outperforms a number of state-of-the-art researches

Large-Scale Fine-Grained Bird Recognition Based on a Triplet Network and Bilinear Model

The main purpose of fine-grained classification is to distinguish among many subcategories of a single basic category, such as birds or flowers. We propose a model based on a triple network and bilinear methods for fine-grained bird identification. Our proposed model can be trained in an end-to-end manner, which effectively increases the inter-class distance of the network extraction features and improves the accuracy of bird recognition. When experimentally tested on 1096 birds in a custom-built dataset and on Caltech-UCSD (a public bird dataset), the model achieved an accuracy of 88.91% and 85.58%, respectively. The experimental results confirm the high generalization ability of our model in fine-grained image classification. Moreover, our model requires no additional manual annotation information such as object-labeling frames and part-labeling points, which guarantees good versatility and robustness in fine-grained bird recognition