Supervised Homography Learning with Realistic Dataset Generation

In this paper, we propose an iterative framework, which consists of two phases: a generation phase and a training phase, to generate realistic training data and yield a supervised homography network. In the generation phase, given an unlabeled image pair, we utilize the pre-estimated dominant plane masks and homography of the pair, along with another sampled homography that serves as ground truth to generate a new labeled training pair with realistic motion. In the training phase, the generated data is used to train the supervised homography network, in which the training data is refined via a content consistency module and a quality assessment module. Once an iteration is finished, the trained network is used in the next data generation phase to update the pre-estimated homography. Through such an iterative strategy, the quality of the dataset and the performance of the network can be gradually and simultaneously improved. Experimental results show that our method achieves state-of-the-art performance and existing supervised methods can be also improved based on the generated dataset. Code and dataset are available at https://github.com/megvii-research/RealSH.Comment: Accepted by ICCV 202

Nonlinear Giant Magnetostrictive Actuator and Its Application in Active Control

The giant magnetostrictive actuator has great use in vibration control, but the linear model cannot fully describe its dynamic characteristics. In this chapter, based on the domain wall theory and piezomagnetic theory, a hysteresis nonlinear model is established to fully describe the actuator dynamic characteristics. In combination with the regularisation method, a sliding mode controller has been designed, and the giant magnetostrictive actuator is also studied in the application of active control. Experimental results show that the hysteresis nonlinear model proposed in the chapter can fully describe the actuator’s dynamic characteristics in a wider frequency band and the active control also has a much better isolation effect than the passive vibration; it can significantly attenuate the external incentives

Comparative investigations of the crystal structure and photoluminescence property of eulytite-type Ba3Eu(PO4)3 and Sr3Eu(PO4)3

In this study, the Ba3Eu(PO4)3 and Sr3Eu(PO4)3 compounds were synthesized and the crystal structures were determined for the first time by Rietveld refinement using powder X-ray diffraction (XRD) patterns. Ba3Eu-(PO4)3 crystallizes in cubic space group I4¯3d, with cell parameters of a = 10.47996(9) Å, V = 1151.01(3) Å3 and Z = 4; Ba2+ and Eu3+ occupy the same site with partial occupancies of 3/4 and 1/4, respectively. Besides, in this structure, there exists two distorted kinds of the PO4 polyhedra orientation. Sr3Eu(PO4)3 is isostructural to Ba3Eu(PO4)3 and has much smaller cell parameters of a = 10.1203(2) Å, V = 1036.52(5) Å3. The bandgaps of Ba3Eu(PO4)3 and Sr3Eu(PO4)3 are determined to be 4.091 eV and 3.987 eV, respectively, based on the UV–Vis diffuse reflectance spectra. The photoluminescence measurements reveal that, upon 396 nm n-UV light excitation, Ba3Eu(PO4)3 and Sr3Eu(PO4)3 exhibit orange-red emission with two main peaks at 596 nm and prevailing 613 nm, corresponding to the 5D0 → 7F1 and 5D0 → 7F2 transitions of Eu3+, respectively. The dynamic disordering in the crystal structures contributes to the broadening of the luminescence spectra. The electronic structure of the hosphates was calculated by the first-principles method. The analysis elucidats that the band structures are mainly governed by the orbits of phosphorus, oxygen and europium, and the sharp peaks of the europium f-orbit occur at the top of the valence bands

Myocardial Stunning-Induced Left Ventricular Dyssynchrony On Gated Single-Photon Emission Computed Tomography Myocardial Perfusion Imaging

Objectives Myocardial stunning provides additional nonperfusion markers of coronary artery disease (CAD), especially for severe multivessel CAD. The purpose of this study is to assess the influence of myocardial stunning to the changes of left ventricular mechanical dyssynchrony (LVMD) parameters between stress and rest gated single-photon emission computed tomography (SPECT) myocardial perfusion imaging (MPI). Patients and methods A total of 113 consecutive patients (88 males and 25 females) who had undergone both stress and rest 99mTc-sestamibi gated SPECT MPI were retrospectively enrolled. Suspected or known patients with CAD were included if they had exercise stress MPI and moderate to severe myocardial ischemia. Segmental scores were summed for the three main coronary arteries according to standard myocardial perfusion territories, and then regional perfusion, wall motion, and wall thickening scores were measured. Myocardial stunning was defined as both ischemia and wall dysfunction within the same coronary artery territory. Patients were divided into the stunning group (n=58) and nonstunning group (n=55). Results There was no significant difference of LVMD parameters between stress and rest in the nonstunning group. In the stunning group, phase SD and phase histogram bandwidth of contraction were significantly larger during stress than during rest (15.05±10.70 vs. 13.23±9.01 and 46.07±34.29 vs. 41.02±32.16, PP\u3c0.05). Conclusion Both systolic and diastolic LVMD parameters deteriorate with myocardial stunning. This kind of change may have incremental values to diagnose CAD

Consistency in Geometry Among Coronary Atherosclerotic Plaques Extracted From Computed Tomography Angiography

Background: The three-dimensional (3D) geometry of coronary atherosclerotic plaques is associated with plaque growth and the occurrence of coronary artery disease. However, there is a lack of studies on the 3D geometric properties of coronary plaques. We aim to investigate if coronary plaques of different sizes are consistent in geometric properties.Methods: Nineteen cases with symptomatic stenosis caused by atherosclerotic plaques in the left coronary artery were included. Based on attenuation values on computed tomography angiography images, coronary atherosclerotic plaques and calcifications were identified, 3D reconstructed, and manually revised. Multidimensional geometric parameters were measured on the 3D models of plaques and calcifications. Linear and non-linear (i.e., power function) fittings were used to investigate the relationship between multidimensional geometric parameters (length, surface area, volume, etc.). Pearson correlation coefficient (r), R-squared, and p-values were used to evaluate the significance of the relationship. The analysis was performed based on cases and plaques, respectively. Significant linear relationship was defined as R-squared > 0.25 and p < 0.05.Results: In total, 49 atherosclerotic plaques and 56 calcifications were extracted. In the case-based analysis, significant linear relationships were found between number of plaques and number of calcifications (r = 0.650, p = 0.003) as well as total volume of plaques (r = 0.538, p = 0.018), between number of calcifications and total volume of plaques (r = 0.703, p = 0.001) as well as total volume of calcification (r = 0.646, p = 0.003), and between the total volumes of plaques and calcifications (r = 0.872, p < 0.001). In plaque-based analysis, the power function showed higher R-squared values than the linear function in fitting the relationships of multidimensional geometric parameters. Two presumptions of plaque geometry in different growth stages were proposed with simplified geometric models developed. In the proposed models, the exponents in the power functions of geometric parameters were in accordance with the fitted values.Conclusion: In patients with coronary artery disease, coronary plaques and calcifications are positively related in number and volume. Different coronary plaques are consistent in the relationship between geometry parameters in different dimensions

Identification of DNA-protein binding residues through integration of Transformer encoder and Bi-directional Long Short-Term Memory

DNA-protein binding is crucial for the normal development and function of organisms. The significance of accurately identifying DNA-protein binding sites lies in its role in disease prevention and the development of innovative approaches to disease treatment. In the present study, we introduce a precise and robust identifier for DNA-protein binding residues. In the context of protein representation, we combine the evolutionary information of the protein, represented by its position-specific scoring matrix, with the spatial information of the protein's secondary structure, enriching the overall informational content. This approach initially employs a combination of Bi-directional Long Short-Term Memory and Transformer encoder to jointly extract the interdependencies among residues within the protein sequence. Subsequently, convolutional operations are applied to the resulting feature matrix to capture local features of the residues. Experimental results on the benchmark dataset demonstrate that our method exhibits a higher level of competitiveness when compared to contemporary classifiers. Specifically, our method achieved an MCC of 0.349, SP of 96.50%, SN of 44.03% and ACC of 94.59% on the PDNA-41 dataset