Automatic Reassembly Method of 3D Thin-wall Fragments Based on Derivative Dynamic Time Warping

In order to address the automatic virtual reassembling of 3D thin-wall fragments, this paper proposes a 3D fragment reassembly method based on derivative dynamic time warping. Firstly, a calculation method of discrete curvature and torsion is designed to solve the difficulty of calculating curvature and torsion of discrete data points and eliminate effectively the noise interferences in the calculation process. Then, it takes curvature and torsion as the feature descriptors of the curve, searches the candidate matching line segments by the derivative dynamic time warping (DDTW) method with the feature descriptors, and records the positions of the starting and ending points of each candidate matching segment. After that, it designs a voting mechanism with the geometric invariant as the constraint information to select further the optimal matching line segments. Finally, it adopts the least squares method to estimate the rotation and transformation matrices and uses the iterative closest point (ICP) method to complete the reassembly of fragments. The experimental results show that the reassembly error is less than 1mm and that the reassembly effect is good. The method can solve the 3D curve matching in case there are partial feature defects, and can achieve the virtual restoration of the broken thin-wall fragment model quickly and effectively

In vitro analysis of phosphorothioate modification of DNA reveals substrate recognition by a multiprotein complex

A wide variety of prokaryotes possess DNA modifications consisting of sequence-specific phosphorothioates (PT) inserted by members of a five-gene cluster. Recent genome mapping studies revealed two unusual features of PT modifications: short consensus sequences and partial modification of a specific genomic site in a population of bacteria. To better understand the mechanism of target selection of PT modifications that underlies these features, we characterized the substrate recognition of the PT-modifying enzymes termed DptC, D and E in a cell extract system from Salmonella. The results revealed that double-stranded oligodeoxynucleotides underwent de novo PT modification in vitro, with the same modification pattern as in vivo, i. e., GpsAAC/GpsTTC motif. Unexpectedly, in these in vitro analyses we observed no significant effect on PT modification by sequences flanking GAAC/GTTC motif, while PT also occurred in the GAAC/GTTC motif that could not be modified in vivo. Hemi-PT DNA also served as substrate of the PT-modifying enzymes, but not single-stranded DNA. The PT-modifying enzymes were then found to function as a large protein complex, with all of three subunits in tetrameric conformations. This study provided the first demonstration of in vitro DNA PT modification by PT-modifying enzymes that function as a large protein complex.National Natural Science Foundation (China) (Grant 31470183)National Natural Science Foundation (China) (Grant 31400029)National Natural Science Foundation (China) (Grant 31170085)National Natural Science Foundation (China) (Grant 30570400)National Natural Science Foundation (China) (Grant 31070058)China. Ministry of Science and Technology (Grant 2012CB721004)China. Ministry of Science and Technology (Grant 2009ZX09501-008)Shanghai Municipal Council of Science and Technology (Shanghai Pujiang Program Grant 12PJD021)China Scholarship CouncilNational Science Foundation (U.S.) (Grant CHE-1019990)National Institute of Environmental Health Sciences (Grant ES002109)Singapore. National Research Foundation (Singapore-MIT Alliance for Research and Technology

Reduced binding activity of vaccine serum to omicron receptor-binding domain

Coronavirus disease 2019 (COVID-19) vaccination regimens contribute to limiting the spread of severe acute respiratory syndrome Coronavirus-2 (SARS-CoV-2). However, the emergence and rapid transmission of the SARS-CoV-2 variant Omicron raise a concern about the efficacy of the current vaccination strategy. Here, we expressed monomeric and dimeric receptor-binding domains (RBDs) of the spike protein of prototype SARS-CoV-2 and Omicron variant in E. coli and investigated the reactivity of anti-sera from Chinese subjects immunized with SARS-CoV-2 vaccines to these recombinant RBDs. In 106 human blood samples collected from 91 participants from Jiangxi, China, 26 sera were identified to be positive for SARS-CoV-2 spike protein antibodies by lateral flow dipstick (LFD) assays, which were enriched in the ones collected from day 7 to 1 month post-boost (87.0%) compared to those harvested within 1 week post-boost (23.8%) (P < 0.0001). A higher positive ratio was observed in the child group (40.8%) than adults (13.6%) (P = 0.0073). ELISA results showed that the binding activity of anti-SARS-CoV-2 antibody-positive sera to Omicron RBDs dropped by 1.48- to 2.07-fold compared to its homogeneous recombinant RBDs. Thus, our data indicate that current SARS-CoV-2 vaccines provide restricted humoral protection against the Omicron variant

Safety evaluation of urban transit signal system based on the improved TOPIS

AbstractSafety evaluation is one of the most effective countermeasures to improve the safety in modern urban transit system. This paper now applies that method to get the order preference of safety in all fault modes in a urban transit signal system using TOPIS based entropy weight for safety evaluation. TOPSIS is based on the concept that the chosen alternative should have the shortest distance from the positive ideal solution (PIS) and the farthest distance from the negative ideal solution (NIS). Entropy weight is ascertained by entropy theory, and the subjectivity in ascertaining the weights of more factors in lower hierarchy is avoided. The evaluation result indicates that this method is easy and can be implemented as an effective method in safety evaluation of urban transit signal system

Regularization solution of Small Baseline Subset Deformation Model Inversion

For the coefficient matrix of the normal equation is ill-conditioned during inverting deformation model of small baseline subset (SBAS) InSAR technique, a regularization robust method is proposed. Based on Tikhonov regularization theory, this method converts the problem of how to solve the deformation rate into minimization problem. According to L-curve method to choose regularization parameter, considering the relationship between the individual components of least-squares residuals to choose regularization matrix, thus it achieves robust solution of SBAS deformation model inversion. We adopt respectively least-squares estimation, ridge estimation and Tikhonov regularization method to deal with 29 ENVISAT ASAR dataset relevant to the Beijing area, achieving the subsidence rate map of the study area. Through comparative analysis among the mean square error (MSE) of 21 points on behalf of the different subsidence, temporal coherence values and MSE maps of the entire study area, we confirm that Tikhonov regularization robust method in inverting SBAS deformation model can obtain more reliable results of deformation monitoring

Efficient Parameters Estimation Method for the Separable Nonlinear Least Squares Problem

In this work, we combine the special structure of the separable nonlinear least squares problem with a variable projection algorithm based on singular value decomposition to separate linear and nonlinear parameters. Then, we propose finding the nonlinear parameters using the Levenberg–Marquart (LM) algorithm and either solve the linear parameters using the least squares method directly or by using an iteration method that corrects the characteristic values based on the L-curve, according to whether or not the nonlinear function coefficient matrix is ill posed. To prove the feasibility of the proposed method, we compared its performance on three examples with that of the LM method without parameter separation. The results show that (1) the parameter separation method reduces the number of iterations and improves computational efficiency by reducing the parameter dimensions and (2) when the coefficient matrix of the linear parameters is well-posed, using the least squares method to solve the fitting problem provides the highest fitting accuracy. When the coefficient matrix is ill posed, the method of correcting characteristic values based on the L-curve provides the most accurate solution to the fitting problem

Optimal selection and application analysis of multi-temporal differential interferogram series in StaMPS-based SBAS InSAR

The optimal selection of multi-temporal differential interferogram series is an important step to monitor ground subsidence using the Stanford method for persistent scatterers (StaMPS)-based small baseline subset (SBAS) interferometric synthetic aperture radar (InSAR). Using a deformation model and its two solution methods, least squares and singular value decomposition, we present the composing mode and optimal selection of multi-temporal differential interferogram series and show that their quality and quantity affect the accuracy of monitored deformation information of SBAS InSAR. Using 29 ENVISAT ASAR images covering urban areas of Beijing, China, a different number of optimal multi-temporal differential interferogram series are formed to monitor urban ground subsidence by the StaMPS-based SBAS method. The comparison and verification of test results indicate that the quality and quantity of multi-temporal differential interferogram series substantially impact the singularity and degree of ill condition of the deformation model, locations of the selected slowly decorrelating filtered phase (SDFP) pixels, and monitored annual mean subsidence velocities. The suitable number of multi-temporal differential interferogram series under the optimal quality is 1–2 for a month in urban ground subsidence monitoring using StaMPS-based SBAS InSAR, a higher quantity of differential interferograms of the optimal quality is not always better

A Method for Solving LiDAR Waveform Decomposition Parameters Based on a Variable Projection Algorithm

Light detection and ranging (LiDAR) is commonly used to create high-resolution maps; however, the efficiency and convergence of parameter estimation are difficult. To address this issue, we evaluated the structural characteristics of received LiDAR signals by decomposing them into Gaussian functions and applied the variable projection algorithm of the separable nonlinear least-squares problem to the process of waveform fitting. First, using a variable projection algorithm, we separated the linear (amplitude) and nonlinear (center position and width) parameters in the Gaussian function model; the linear parameters are expressed with nonlinear parameters by the function. Thereafter, the optimal estimation of the characteristic parameters of the Gaussian function components was transformed into a least-squares problem only comprising nonlinear parameters. Finally, the Levenberg–Marquardt algorithm was used to solve these nonlinear parameters, whereas the linear parameters were calculated simultaneously in each iteration, and the estimation results satisfying the nonlinear least-square criterion were obtained. Five groups of waveform decomposition simulation data and ICESat/GLAS satellite LiDAR waveform data were used for the parameter estimation experiments. During the experiments, for the same accuracy, the separable nonlinear least-squares optimization method required fewer iterations and lesser calculation time than the traditional method of not separating parameters; the maximum number of iterations was reached before the traditional method converged to the optimal estimate. The method of separating variables only required 14 iterations to obtain the optimal estimate, reducing the computational time from 1128 s to 130 s. Therefore, the application of the separable nonlinear least-squares problem can improve the calculation efficiency and convergence speed of the parameter solution process. It can also provide a new method for parameter estimation in the Gaussian model for LiDAR waveform decomposition

Sensitivity and reliability analysis to MSBAS regularization for the estimation of surface deformation over a mine

AbstractTo systematically and thoroughly analyze the sensitivity and reliability of the MSBAS regularization for the estimation of surface deformation over a mine in combination with an application example, this study processed 101 Sentinel-1A/B SAR images, constructed and solved the 2D deformation models using SVD and Tikhonov regularization methods with different orders and parameters, and estimated the vertical and east-west surface deformation time series in a mine of China. Then, this study collected the leveling-monitoring vertical surface deformation data on three leveling points, and compared and analyzed the sensitivity and reliability of the MSBAS regularization methods for estimating vertical surface deformation. The results indicate that different regularization orders and parameters can lead to thousands of times differences in condition numbers and significant differences in ill-posed degree of the deformation models. The zero-order Tikhonov regularized deformation model with regularization parameter of 0.1 has the minimum condition number and the equation is not ill-posed. The first-order Tikhonov regularized deformation model with regularization parameter of 0.001 has the maximum condition number and the equation is seriously ill-posed. As a result, the estimates of 2D surface deformation models with different parameters and orders are also different in terms of numerical values and accuracy. Compared with the leveling-monitoring data, the first- and second-order MSBAS regularization methods with parameter 0.1 have the minimum fluctuation and the maximum correlation coefficients between the estimated values and the leveling-monitoring values, and are also closest to the leveling-monitoring results with the highest accuracy

Accuracy Verification and Correction of D-InSAR and SBAS-InSAR in Monitoring Mining Surface Subsidence

The accuracy of InSAR in monitoring mining surface subsidence is always a matter of concern for surveyors. Taking a mining area in Shandong Province, China, as the study area, D-InSAR and SBAS-InSAR were used to obtain the cumulative subsidence of a mining area over a multi-period, which was compared with the mining progress of working faces. Then dividing the mining area into regions with different magnitudes of subsidence according to the actual mining situation, the D-InSAR-, SBAS-InSAR- and leveling-monitored results of different subsidence magnitudes were compared and the Pearson correlation coefficients between them were calculated. The results show that InSAR can accurately detect the location, range, spatial change trend, and basin edge information of the mining subsidence. However, InSAR has insufficient capability to detect the subsidence center, having high displacement rates, and its monitored results are quite different from those of leveling. To solve this problem, the distance from each leveling point to the subsidence center was calculated according to the layout of the rock movement observation line. Besides, the InSAR-monitored error at each leveling point was also calculated. Then, according to the internal relationship between these distances and corresponding InSAR-monitored errors, a correction model of InSAR-monitored results was established. Using this relationship to correct the InSAR-monitored results, results consistent with the actual situation were obtained. This method effectively makes up for the deficiency of InSAR in monitoring the subsidence center of a mining area