Dynamic 3D shape measurement based on the phase-shifting moir\'e algorithm

In order to increase the efficiency of phase retrieval,Wang proposed a high-speed moire phase retrieval method.But it is used only to measure the tiny object. In view of the limitation of Wang method,we proposed a dynamic three-dimensional (3D) measurement based on the phase-shifting moire algorithm.First, four sinusoidal fringe patterns with a pi/2 phase-shift are projected on the reference plane and acquired four deformed fringe patterns of the reference plane in advance. Then only single-shot deformed fringe pattern of the tested object is captured in measurement process.Four moire fringe patterns can be obtained by numerical multiplication between the the AC component of the object pattern and the AC components of the reference patterns respectively. The four low-frequency components corresponding to the moire fringe patterns are calculated by the complex encoding FT (Fourier transform) ,spectrum filtering and inverse FT.Thus the wrapped phase of the object can be determined in the tangent form from the four phase-shifting moire fringe patterns using the four-step phase shifting algorithm.The continuous phase distribution can be obtained by the conventional unwrapping algorithm. Finally, experiments were conducted to prove the validity and feasibility of the proposed method. The results are analyzed and compared with those of Wang method, demonstrating that our method not only can expand the measurement scope, but also can improve accuracy.Comment: 14 pages,5 figures. ams.or

Fresnel diffraction patterns as accelerating beams

We demonstrate that beams originating from Fresnel diffraction patterns are self-accelerating in free space. In addition to accelerating and self-healing, they also exhibit parabolic deceleration property, which is in stark contrast to other accelerating beams. We find that the trajectory of Fresnel paraxial accelerating beams is similar to that of nonparaxial Weber beams. Decelerating and accelerating regions are separated by a critical propagation distance, at which no acceleration is present. During deceleration, the Fresnel diffraction beams undergo self-smoothing, in which oscillations of the diffracted waves gradually focus and smooth out at the critical distance

Association between sleep-disordered breathing and periodontitis:a meta-analysis

Systemic inflammation is a feature of sleep-disordered breathing (SDB) as well as periodontitis. The association between SDB and periodontitis, however, has been inconsistent in previous studies. In order to fully evaluate the above association, we conducted a meta-analysis. Observational studies related to the aim of the meta-analysis were identified by search of PubMed, Embase, Web of Science, Wanfang, and CNKI databases. Only studies with SDB diagnosed with the objective polysomnography examination were included. The results were analyzed using a random-effects model that incorporated potential heterogeneity between studies. Ten cross-sectional or case-control studies with 43,296 participants contributed to the meta-analysis. Pooled results showed that SDB was significantly associated with periodontitis (odds ratio [OR]: 1.83, 95% confidence interval [CI]: 1.52 to 2.20, I2 = 40%, p < 0.001). Sensitivity analysis showed consistent association for severe periodontitis (OR: 1.39, 95% CI: 1.20 to 1.61, I2 = 0%, p < 0.001). Subgroup analyses showed consistent results in patients with mild (OR: 1.66, p < 0.001), moderate (OR: 2.23, p = 0.009), and severe SDB (OR: 2.66, p < 0.001). Moreover, the association between SDB and periodontitis was consistent in Asian and non-Asian studies, in cross-sectional and case-control studies, in studies with univariate and multivariate regression models, and in studies with different quality scores (p for subgroup effects all < 0.05). Polysomnography confirmed diagnosis of SDB is associated with periodontitis in adult population

DoubleH: Twitter User Stance Detection via Bipartite Graph Neural Networks

Given the development and abundance of social media, studying the stance of social media users is a challenging and pressing issue. Social media users express their stance by posting tweets and retweeting. Therefore, the homogeneous relationship between users and the heterogeneous relationship between users and tweets are relevant for the stance detection task. Recently, graph neural networks (GNNs) have developed rapidly and have been applied to social media research. In this paper, we crawl a large-scale dataset of the 2020 US presidential election and automatically label all users by manually tagged hashtags. Subsequently, we propose a bipartite graph neural network model, DoubleH, which aims to better utilize homogeneous and heterogeneous information in user stance detection tasks. Specifically, we first construct a bipartite graph based on posting and retweeting relations for two kinds of nodes, including users and tweets. We then iteratively update the node's representation by extracting and separately processing heterogeneous and homogeneous information in the node's neighbors. Finally, the representations of user nodes are used for user stance classification. Experimental results show that DoubleH outperforms the state-of-the-art methods on popular benchmarks. Further analysis illustrates the model's utilization of information and demonstrates stability and efficiency at different numbers of layers

Anomalous wavefront control via nonlinear acoustic metasurface through second-harmonic tailoring and demultiplexing

We propose a nonlinear acoustic metasurface concept by exploiting the nonlinearity of the locally resonant unit cells formed by curved beams. The analytical model is established to explore the nonlinear phenomenon, specifically the second-harmonic generation (SHG) of the acoustic waveguide and validated through numerical and experimental studies. Novel nonlinear acoustic metasurfaces are developed to demultiplex different frequency components and achieve anomalous wavefront control of SHG in the transmitted region. To this end, we demonstrate wave steering, wave focusing, and self-bending propagation. Our results show that the proposed nonlinear metasurface provides an effective and efficient platform to achieve significant SHG, and separate different harmonic components for wavefront control of individual harmonics. Overall, this study offers new avenues to harness nonlinear effects for acoustic wavefront tailoring and develops new potential toward advanced technologies to manipulate acoustic waves