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Point set registration is one of the challenging tasks in remote sensing image processing and analysis. Its critical step is to find the corresponding relationships between the fixed scene point set and the moving model point set that undergo different sorts of transformations. Existing algorithms primarily utilize different types of prior information to improve the registration performance, such as spatial consistency, local similarity, and uniform outliers. However, due to the lack of active evaluation on the prior and intermediate information during the registration process, these strategies are susceptible to large data transformations. In order to enhance the robustness and accuracy for point set registration, we propose in this article a novel framework, namely Registration-is-Evaluation (RisE). Based on a multigranular probability model, our method exploits and utilizes both prior and posterior information to dynamically evaluate the matching status. What is more, instead of adding an extra uniform prior, we unified the outliers, noise, missing points, and heavily warped points into our registration evaluation model and address them simultaneously. We also apply a novel point set descriptor, called local polar relative geometry (LPRG), to have a more robust local similarity measurement. It adopts the local polar coordinate to perform multiscale pooling and relative geometric computation. Based on our proposed method, the matching relationships and the spatial transformations can be actively evaluated to provide useful contextual guidance for the registration process. Experimental results on multiple data sets show that our algorithm outperforms the state-of-the-art methods, in terms of both accuracy and robustness under large data degradations.

Sensor-based Human Activity Recognition (HAR) requires the acquisition of Channel State Information(CSI) data with time series based on sensors to predict human behavior. Many existing approaches are based on wearable sensors and cameras, which increase the burden and privacy issues for patients. Selfpowered sensors are capable of non-contact collection of time series data generated by human activity while ensuring their own stable operation. In this paper, we propose a deep learning-based framework for contactless real-time activity detection of humans using self-powered sensors, which is called Multilayer Bi-directional Long Short-Term Memory (MBLSTM). The collected WIFI CSI data are fed into our proposed network model, which is then used to learn representative features of both sides from the original continuous CSI measurements. And the attention model is used to assign different weights to the learned features, and finally activity recognition is performed. Experimental results show that our proposed method achieves an accuracy of more than 96% for the recognition of six activities in multiple rounds of testing, outperforming other benchmark methods used for comparison.

Ti47Cu38−xZr7.5Fe2.5Sn2Si1Ag2Pdx (x = 1, 2, 3, and 4 atomic percent, at. pct) bulk metallic glasses (BMGs) with potential for biomedical applications were fabricated by copper-mold casting. The Ti-based BMGs exhibited high glass-forming ability (GFA) with critical diameters of 4 to 5 mm and a supercooled liquid region over 50 K, though the high contents of Pd slightly decreased the GFA. The additions of 2 and 3 at. pct Pd benefited the improvement of plasticity, and the resultant BMGs showed the relatively low Young’s modulus of about 100 GPa, high compressive strengths of 2174 to 2340 MPa, and compressive plastic strain of around 4 pct. The addition of Pd also decreased the passive current density and increased the pitting potential of the Ti-based BMGs in the Hank’s solution, leading to the enhanced bio-corrosion resistance of the BMGs. Furthermore, the cell adhesion, viability, and proliferation behaviors revealed that the present Ti-based BMGs possess as good biocompatibility as that of the Ti-6Al-4V alloy. These results demonstrated the potential of the Ti-Cu-Zr-Fe-Sn-Si-Ag-Pd BMGs as biomedical materials.

The wear, elastic, mechanical and thermodynamic properties of bulk metallic glasses (BMGs) is studied to explore correlations between the wear resistance and properties of BMGs. It is found that the wear resistance of BMGs is dominated by synergistic effects of strength factors, namely the hardness (H), Young's modulus (E), yield strength (σy) and glass transition temperature (Tg), as well as toughness factors, like the notch toughness (KQ) and Poisson's ratio (ν). Moreover, a novel strategy for optimizing the wear resistance of BMGs is proposed from elastic perspective. The wear resistance of BMGs is correlated with chemistry-induced changes to bulk modulus (B) and Poisson's ratio (ν) for the first time. Developing BMGs with high value of B 0.5 · [ 2 ( 1 + v ) / 3 ( 1 − 2 v ) ] 0.25 can achieve simultaneously both high strength and good toughness, which provides the elastic opportunities for designing ultra-wear-resistant BMGs.

In this study, the influences of Pd, Au and Pt on the glass-forming ability (GFA), mechanical property, electrochemical behavior and tribocorrosion resistance of the Ni- and Cu-free Zr53Al16Co31 bulk metallic glass (BMG) were investigated. Alloying of noble elements enhances the GFA and the Zr53Al16Co26M5 (M = Pd, Au and Pt) BMGs with a diameter of 5 mm can be fabricated by copper mold casting. The ZrAlCo-based BMGs show a good combination of mechanical properties with a high yield strength of over 2000 MPa, low Young's modulus of about 93 GPa and high hardness of over 550 HV. Pd, Au and Pt take a significant influence on the corrosion resistance of the ZrAlCo-based BMGs in phosphate buffer saline (PBS) solution. The ZrAlCoPt alloy exhibits the highest corrosion resistance whereas ZrAlCoAu displays the lowest one, which can be correlated with their Zr and Al concentration in the surface passive film of alloys. The ZrAlCo-based BMGs illustrate a lower wear resistance in PBS solution than that in air, which is attributed to the synergistic effects of abrasive and corrosive wear. The wear resistance of ZrAlCo-based BMGs in PBS solution highly corresponds to their corrosion resistance. The ZrAlCoPt alloy demonstrates the highest tribocorrosion resistance while ZrAlCoAu shows the lowest one among these four ZrAlCo-based BMGs. The possible mechanism of corrosion accelerating wear deterioration is discussed, which provides the guidance for the improvement in the tribocorrosion resistance of Zr-based BMGs for their promising biomedical applications.

Point set registration is one of the challenging tasks in computer vision. One critical step is to find the corresponding relationship between the model point set and the scene point set. Existing registration algorithms primarily utilize the information of global and local shape, yet neglect the credibility of corresponding relation, therefore they may lead to the insufficient estimation of spatial transformation. To tackle this problem, we firstly adopt a relative polar coordinate system, it performs spatial pooling operation and further divides the feature extraction region into sub-areas with different scales. Then, based on the Relative Average Distance (RAD) and the Relative Average Offset Angle (RAOA), we propose multi-granular MRGS descriptor to extract visual structures of the point set. The similarity between the model point set and scene point set is then represented by the Gaussian Mixture Model, where the weights can be dynamically adjusted during the process of registration. Finally, we apply the robust mixture re-weighting to reduce the impact of false corresponding pairs and reinforce the weight of correct matching points. Experimental results on synthetic data and medical image data not only show that our method outperform state-of-the-art methods, but also demonstrate the robustness of our method when the non-grid transformation of point sets suffers from deformations, noises and outliers.

The mechanical, electrochemical, wear, and corrosive-wear behaviors of a TiZrCuPd bulk glassy alloy were investigated. The Ti-based glassy alloy demonstrates a high yield strength of 2.3 GPa, low Young's modulus of 95 GPa, and Vickers microhardness of 7.2 GPa, which are superior to those of the Ti-6Al-4V biomedical alloy. The TiZrCuPd glassy alloy shows a good corrosion resistance in the phosphate buffer saline (PBS) solution, owing to the formation the Ti- and Zr-enriched passivation film on the alloy surface. The TiZrCuPd alloy displays the lowdry-wear rate of 6.1 × 10−8 mm3 mm N−1and wet-wear rate of 8.0 × 10−8 mm3 mm N−1. The triobocorrosionresults illustrate that the TiZrCuPd alloyshows a high pitting corrosion resistance during the wet sliding, which render its good corrosive wear performance. The good combination of mechanical, corrosion, and wear properties of the Ti-based glassy alloy make it promising for biomedical applications.

Wear behaviors of the FeCoCrMoCBY bulk metallic glass (BMG), 316 L stainless steel (SS), and CoCrMo alloy under wet sliding in the phosphate buffered saline (PBS) solution were studied and compared with those under dry sliding. The Fe-based BMG exhibited an excellent corrosive wear resistance with a low wear rate of 1.84 × 10−8 mm3 mm−1•N − 1. On the contrary, the CoCrMo alloy and 316 L SS suffered from the synergistic effect of corrosion and wear in the PBS solution. The electrochemical results revealed that the Fe-based BMG possessed the greatest corrosion performance in the PBS solution among three alloys. The excellent corrosion behavior of the Fe-based BMG was attributed to the highly-protective surface passivation film enriched in Cr and Mo elements. The triobocorrosion results manifested that the great anti-corrosive-wear capacity of the Fe-based BMG can be ascribed to the high stable passivation process during wet sliding.

The effects of heat treatment on the microstructures, crystallization kinetics, mechanical performance, and anti-corrosion behavior of a hypoeutectic Zr68Al8Ni8Cu16 bulk metallic glass (BMG) were studied. Through annealing, the precipitated phases were crystalline Zr2Cu and Zr2Ni. The total crystallinity was determined to be 10% and 77% for the samples annealed at 673 K and 713 K, respectively. The partial crystallization of the alloy leads to a dramatic deterioration in the ductility as compared to the as-cast BMG. Furthermore, the decrease in the ductility was accompanied by an increase in the crystallinity. The as-cast Zr-based BMG exhibited a greater corrosion resistance in the HCl solution than that of the annealed alloy. The depletion in the Zr and Al cation fractions of the surface oxidation film, which resulted from the precipitation of reactive nanocrystalline phases from the glassy matrix, is responsible for the reduced corrosion resistance.

The present study prepares novel Zr70+xAl5Fe15-xNb10 (x=0, 5) alloys by arc-melting for potential biomedical application. The mechanical properties and bio-tribological behaviors of the Zr-based alloys are evaluated and compared with biomedical pure Zr. The as-prepared alloys exhibit a microstructure containing a micrometer-sized dendritic beta-Zr phase dispersed in a Zr2Fe-typed matrix. It is found that increasing the content of Zr is favorable for the mechanical compatibility with a combination of low Young's modulus, large plasticity, and high compressive strength. The wear resistance of the Zr-Al-Fe-Nb alloys in air and phosphate buffer saline (PBS) solution is superior to that of pure Zr. The wear mechanism of Zr-based alloys sliding in air is controlled by oxidation and abrasive wear whereas that sliding in PBS is controlled by synergistic effects of the abrasive and corrosive wear. Electrochemical measurements demonstrate that the Zr-based alloys are corrosion resistant in PBS. Their bio-corrosion resistance is improved with the increase in Zr content, which is attributed to the enrichment in Zr and decrease in Al concentration in the surface passive film of alloys. The Zr75Al5Fe10Nb10 exhibits the best corrosion resistance in PBS, which contributes to its superior wear resistance in a simulated body environment. The combination of good mechanical properties, corrosion resistance, and biotribological behaviors of the Zr-Al-Fe-Nb alloys offers them potential advantages in biomedical applications.