TC-SfM: Robust Track-Community-Based Structure-From-Motion.

Structure-from-Motion (SfM) aims to recover 3D scene structures and camera poses based on the correspondences between input images, and thus the ambiguity caused by duplicate structures (i.e., different structures with strong visual resemblance) always results in incorrect camera poses and 3D structures. To deal with the ambiguity, most existing studies resort to additional constraint information or implicit inference by analyzing two-view geometries or feature points. In this paper, we propose to exploit high-level information in the scene, i.e., the spatial contextual information of local regions, to guide the reconstruction. Specifically, a novel structure is proposed, namely, track-community, in which each community consists of a group of tracks and represents a local segment in the scene. A community detection algorithm is performed on the track-graph to partition the scene into segments. Then, the potential ambiguous segments are detected by analyzing the neighborhood of tracks and corrected by checking the pose consistency. Finally, we perform partial reconstruction on each segment and align them with a novel bidirectional consistency cost function which considers both 3D-3D correspondences and pairwise relative camera poses. Experimental results demonstrate that our approach can robustly alleviate reconstruction failure resulting from visually indistinguishable structures and accurately merge the partial reconstructions.

Size, composition, and surface capping-dependent catalytic activity of spherical gold nanoparticles.

Gold nanostructures are used as catalysts in heterogeneous catalytic processes and have intrigued chemists and materials scientists. Isotropic spherical gold nanoparticles (AuNPs) are ideal for catalysis due to their simple preparation process, controllable surface-active site, tunable size, and composition-dependent catalytic activity. In this study, spherical AuNPs with different size, composition, and surface capping agents have been prepared, and their catalytic activity in reduction of 4-nitrophenol (4-NP) is evaluated. The catalytic activity of AuNPs decreases as their size increases. Meanwhile, the catalytic activity of AuNPs with tartrate as the reducing agent show no evident changes because of containing anisotropic AuNPs. Moreover, silver not only improves monodisperse and spherical AuNPs, but also increases the catalytic activity of small AuNPs. Since the molecular structures of tartrate and citrate are similar, there is no remarkable difference in the catalytic activity of AuNPs using tartrate and citrate as capping agents. These results demonstrate the influence of size, composition, and surface capping on the catalytic activity of AuNPs. Overall, this study facilitates the applicability of gold-based catalyst and AuNPs in plasmonics, nanophotonics, biomedical photonics, and photocatalysis.

Risk assessment for tailings dams in Brumadinho of Brazil using InSAR time series approach.

Tailings dams are usually ponds bounded by valleys or surrounding topography to store mining or other chemical industrial waste. On 25 January 2019, the collapse of a tailings dam at the Córrego do Feijao iron ore mine (Brumadinho, Minas Gerais, Brazil) released about 12 million m3 of tailings, killing over 240 people and posing a considerable and ongoing environmental threat. The stability of tailings dam monitoring is very important and in the present paper, a new InSAR (Synthetic Aperture Radar Interferometry) time series approach is proposed to derive ground displacement maps for use in dam safety monitoring. Compared with the other solutions, the unique feature of the proposed method is that: 1) the new Measurement Pixel (MP) selection criteria has the potential to include relatively more accurate MP pixels and build a more robust network, 2) the multi-level grading system makes it possible to add the MP pixels into the main network step-by-step with external control, and 3) the computing efficiency can be improved by strategically reducing the iteration times. The proposed approach was tested on both simulated and real data. Results show that the Simulated Annealing (SA) method normally has a more accurate estimation as compared to the Quasi-Newton (QN) method, despite its longer processing time. Detailed analysis of the displacement maps was conducted to determine the subsidence processes that result from dam construction.

SCF/SCFR signaling plays an important role in the early morphogenesis and neurogenesis of human embryonic neural retina.

The stem cell factor receptor (SCFR) has been demonstrated to be expressed in the neural retina of mice, rat and human for decades. Previous reports indicated that the SCFR correlates with glia differentiation of late retinal progenitor cells (RPCs), retinal vasculogenesis and homeostasis of the blood-retinal barrier. However, the role of SCF/SCFR signaling in the growth and development of the neural retina (NR), especially in the early embryonic stage, remains poorly understood. Here, we show that SCF/SCFR signaling orchestrates invagination of the human embryonic stem cell (hESC)-derived NR via regulation of cell cycle progression, cytoskeleton dynamic and apical constriction of RPCs in the ciliary marginal zone (CMZ). Furthermore, activation of SCF/SCFR signaling promotes neurogenesis in the central-most NR via acceleration of the migration of immature ganglion cells and repressing apoptosis. Our study reveals an unreported role for SCF/SCFR signaling in controlling ciliary marginal cellular behaviors during early morphogenesis and neurogenesis of the human embryonic NR, providing a new potential therapeutic target for human congenital eye diseases such as anophthalmia, microphthalmia and congenital high myopia.

A Novel General Imaging Formation Algorithm for GNSS-Based Bistatic SAR.

Global Navigation Satellite System (GNSS)-based bistatic Synthetic Aperture Radar (SAR) recently plays a more and more significant role in remote sensing applications for its low-cost and real-time global coverage capability. In this paper, a general imaging formation algorithm was proposed for accurately and efficiently focusing GNSS-based bistatic SAR data, which avoids the interpolation processing in traditional back projection algorithms (BPAs). A two-dimensional point target spectrum model was firstly presented, and the bulk range cell migration correction (RCMC) was consequently derived for reducing range cell migration (RCM) and coarse focusing. As the bulk RCMC seriously changes the range history of the radar signal, a modified and much more efficient hybrid correlation operation was introduced for compensating residual phase errors. Simulation results were presented based on a general geometric topology with non-parallel trajectories and unequal velocities for both transmitter and receiver platforms, showing a satisfactory performance by the proposed method.

A User Authentication Scheme Based on Elliptic Curves Cryptography for Wireless Ad Hoc Networks.

The feature of non-infrastructure support in a wireless ad hoc network (WANET) makes it suffer from various attacks. Moreover, user authentication is the first safety barrier in a network. A mutual trust is achieved by a protocol which enables communicating parties to authenticate each other at the same time and to exchange session keys. For the resource-constrained WANET, an efficient and lightweight user authentication scheme is necessary. In this paper, we propose a user authentication scheme based on the self-certified public key system and elliptic curves cryptography for a WANET. Using the proposed scheme, an efficient two-way user authentication and secure session key agreement can be achieved. Security analysis shows that our proposed scheme is resilient to common known attacks. In addition, the performance analysis shows that our proposed scheme performs similar or better compared with some existing user authentication schemes.

Noise Reduction in ECG Signal Based on Adaptive Wavelet Transform.

Noise always influences on the result of signal-detection, therefore it is a hot topic to detect signal under the low signal-to-noise ratio (SNR) in current detection field. However, it is an intractable problem of signal-detection to extract weak signal under a high noisy environment. Adaptation filter provides a simple and useful way to detect signal. Through measuring and studying, it is possible to carry out the best combination of weak signal under the condition of weak signal. In this paper, we propose a novel mechanism to detect the ECG signal based on adaptation wavelet transform (WT). We adopt the sub-strap coded theory of WT and restore post-combination weak signal through adaptation matching of multi sub-straps' weights. The simulation results show that the proposed method can further improve the ability to detect signal, which is a very effective scheme to detect the property of weak signal and improve SNR.

Detection of ECG Signal Based on Multi-resolution Sub-band Filter.

A high noisy environment severely contaminates the ECG signal. In this paper, the use of a wavelet transform domain filtering technique as an adaptive de-noising tool, implemented in ECG signal analysis, is presented. The multi-resolution representations of the signal, produced by wavelet transform (WT), are used for signal structure extraction. Experimental results have shown that the implementation of this wavelet-based filter in ECG signal analysis results in an efficient reduction of the high noisy environment, producing an almost noise-free output signal. Due to its simplicity and its fast implementation the method can easily be used in clinical medicine.