Linear Alignment Research Articles

Fault diagnosis of high-speed train suspension systems using multiscale permutation entropy and linear local tangent space alignment

Online health monitoring of railway vehicle suspension systems is of critical importance to guarantee train running safety. The currently reported works on vehicle suspension health monitoring mainly adopt model-based approaches. However, detailed parameters of the vehicle suspension systems, usually, are complicated to be acquired. Moreover, an accurate model cannot be easily obtained due to the nonlinearities of vehicle components and the complexity of suspension systems. Considering the limitations of the model-based approaches, a data-driven method, which combines multiscale permutation entropy and linear local tangent space alignment (MPE-LLTSA), is proposed to diagnose the faults of vehicle suspension systems. To demonstrate the effectiveness and advantages of this method, an MBS model of the China CRH3 train is built to generate the bogie frame’s lateral acceleration containing various secondary suspension faults, and the simulated signals are then introduced to evaluate the MPE-LLTSA method. The evaluation results show that the proposed data-driven approach can accurately identify different types of suspension faults. Finally, the MPE-LLTSA method is further validated using the tracking data of the CRH3 train running on a high-speed railway line in China, and the test results show that the proposed method has the potential to be applied to the field of railway engineering.

Intrinsic alignment statistics of density and velocity fields at large scales: Formulation, modeling, and baryon acoustic oscillation features

The kinematic Sunyaev-Zel'dovich effect enables us to directly probe the density-weighted velocity field up to very large cosmic scales. We investigate the effects of intrinsic alignments (IAs) of dark-matter halo shapes on cosmic density and velocity fields on such large scales. In the literature IAs have been detected up to $\sim 100~h^{-1}{\rm Mpc}$ using the gravitational shear-intrinsic ellipticity correlation and the alignment correlation function. In this paper we introduce the corresponding various velocity statistics: the (density-weighted) velocity-intrinsic ellipticity correlation as well as the alignment pairwise infall momentum, momentum correlation function, and density-weighted pairwise velocity dispersion. We derive theoretical expressions for these velocity alignment statistics for the first time based on the assumption that the density fluctuation is a Gaussian random field. Using large-volume, high-resolution $N$-body simulations, we measure the alignment statistics of density and velocity fields. The behaviors of IAs in the velocity statistics are similar to those in the density statistics, except that the halo orientations are aligned with the velocity field up to scales larger than those with the density field, $r\gg 100~h^{-1}{\rm Mpc}$, because of a factor of the wave number in the linear relation between the density and velocity fields in Fourier space, $v\propto \delta/k$. We show that the detected IAs of the velocity field can be well predicted by the linear alignment model. We also demonstrate that the baryon acoustic oscillation features can be detected in both the conventional and alignment velocity statistics. Our results indicate that observations of IAs with the velocity field on large scales can provide additional information on cosmological models, complementary to those with the density field.

Precision Nanotube Mimics via Self-Assembly of Programmed Carbon Nanohoops.

The scalable production of homogeneous, uniform carbon nanomaterials represents a key synthetic challenge for contemporary organic synthesis as nearly all current fabrication methods provide heterogeneous mixtures of various carbonized products. For carbon nanotubes (CNTs) in particular, the inability to access structures with specific diameters or chiralities severely limits their potential applications. Here, we present a general approach to access solid-state CNT mimic structures via the self-assembly of fluorinated nanohoops, which can be synthesized in a scalable, size-selective fashion. X-ray crystallography reveals that these CNT mimics exhibit uniform channel diameters that are precisely defined by the diameter of their nanohoop constituents, which self-assemble in a tubular fashion via a combination of arene-pefluoroarene and C-H-F interactions. The nanotube-like assembly of these systems results in capabilities such as linear guest alignment and accessible channels, both of which are observed in CNTs but not in the analogous all-hydrocarbon nanohoop systems. Calculations suggest that the organofluorine interactions observed in the crystal structure are indeed critical in the self-assembly and robustness of the CNT mimic systems. This work establishes the self-assembly of carbon nanohoops via weak interactions as an attractive means to generate solid-state materials that mimic carbon nanotubes, importantly with the unparalleled tunability enabled by organic synthesis.

Pixels and 3-D Points Alignment Method for the Fusion of Camera and LiDAR Data

The fusion of light detection and ranging (LiDAR) and camera data is a promising approach to improve the environmental perception and recognition for intelligent vehicles because of the combination of depth and color information. One of the difficulties in achieving the fusion is the accurate alignment of the 3-D points with the image pixels. Current methods of data alignment involve the steps of estimating the camera intrinsic parameters and developing a transformation matrix between the camera and LiDAR frame. The drawback of these methods is the accumulation of errors during the calculation of the camera intrinsic parameters and the transformation matrix. In order to improve the data alignment accuracy, we propose a novel algorithm that directly calculates the alignment between the 3-D points and the pixels without the need for camera parameters and calibration of the coordinate transformation matrix. We call the proposed method the pixel and 3-D point alignment (PPA) method. The alignment procedure is achieved by using the extracted corresponding points. First, we calculate a linear alignment matrix without considering the image distortion; and second, we optimize the parameters using the maximum likelihood estimation to consider the camera distortion. Simulation and experimental results indicate that the PPA method is able to align the 3-D points in LiDAR frame with the pixels in image frame with higher accuracy and increased robustness against noise in calibration process than comparable state-of-the-art methods.

HYPOTHETICAL LEARNING TRAJECTORY IN REALISTIC MATHEMATICS EDUCATION TO IMPROVE THE MATHEMATICAL COMMUNICATION OF JUNIOR HIGH SCHOOL STUDENTS

This research was motivated by the difficulties of junior high school students in linear equation system material. The focus of this research is to produce the Hypothetical Learning Trajectory (HLT) system of linear equations based on the development of Learning Trajectory (LT) with the aim of research to improve students' mathematical communication skills. Research method used design Research with 3 phases: Preliminary design, teaching experiment, and retrospective analysis. The subject of study in SMP grade VII in Tasikmalaya district. This research uses the instrument of communication skills test students. Processing of research data using test-T. Based on the results of the research obtained: (a) HLT results from the development of LT linear alignment system in RME to improve student mathematical communication skills; and (b) students who acquire RME learning have increased mathematical communication skills greater than those who acquire conventional learning.

Visualisation of impacts due to the proposed developmental projects in the ecologically fragile regions- Kodagu district, Karnataka

Assessing land use land cover changes in forested regions reflect the extent of anthropogenic pressure, ecosystem degradation and their impact on local wellbeing. The rapid expansion of linear developments such as roads, power lines will have an irreversible loss of habitat, as a result of forest fragmentation and consequent disruptions in the local ecological processes. The spatiotemporal land use analysis of Kodagu highlights the loss of forest cover due to an uncontrolled expansion of coffee plantations and other driving forces. The major cover of evergreen forest (40.47 to 27.14%) has lost due to interventions in terms of road, built-up areas and other changes. Around 66,892 ha of pristine forest cover was lost due to un-interrupted exploitation. Kushalnagara and Madikere taluks have lost the major chunk of forests due to construction (roads, homestays, villas, etc.) activities. Forest fragmentation analyses portray the status of forests in their condition across the temporal scale. The region had 32% of forest cover under interior or intact forests in 1973, whereas in 2018 it covers only 19% under various protected areas. Though Kodagu district is well connected with national and state high ways, the Government has now proposed to increase the road width of existing major highways (7) and a new railway line connecting Tellicherry and Mysore. The scenario based analysis has been done considering business as usual and with the expansion of linear alignments using Fuzzy-MCE-AHP-MCA. Forecasting future land use changes resulting from linear developments suggest the loss of core forest with the expansion of pre-existing roads. The loss of 8% forest cover with the expansion of linear alignments will have irreversible impacts on Kodagu landscape. The study reveals the causal factors for the disaster are the absence of prudent management of a landscape in the ecologically fragile region evident from the conversion of native forests to other land uses, disruption of stream network, construction of buildings along the water course disrupting the natural water flow, construction or expansion of existing roads, steep vertical cuts leading to structural instability, removal of native vegetation cover in highly undulating terrains with steep slopes leading to the weakening of terrain due to the lowered binding capability of soil, encroachment of local water bodies (such as ponds/tanks), etc. The study emphasizes the need for restoration of stream network, catchment treatment through planting of native species, arresting deforestation and restrictions of large-scale developmental projects with the detrimental land use changes. The outcome of the current research helps in evolving appropriate policies to review the proposed linear projects towards sustainable management of natural resources.

Rolling bearing fault diagnosis based on adaptive smooth ITD and MF-DFA method

To effectively utilize a feature set to further improve fault diagnosis of a rolling bearing vibration signal, a method based on multi-fractal detrended fluctuation analysis (MF-DFA) and smooth intrinsic time-scale decomposition (SITD) was proposed. The vibration signal was decomposed into several proper rotation components by applying this new SITD method to overcome noise effects, preserve the effective signal, and improve the signal-to-noise ratio. Wavelet analysis was embedded in iteration procedures of intrinsic time-scale decomposition (ITD). For better results, an adaptive threshold function was used for signal recovery from noisy proper rotation components in the wavelet domain. Additionally, MF-DFA was used to reveal the multi-fractality present in the instantaneous amplitude of the proper rotation components. Finally, linear local tangent space alignment was applied for feature dimension reduction and to obtain fault characteristics of different types, further improving identification accuracy. The performance of the proposed method is determined to be superior to that of the ITD-MF-DFA method.

Research on improved fine alignment methods

Based on the hypothesis of small values of misalignment angles, compass alignment and linear Kalman alignment are common fine alignment methods. The algorithm of compass alignment has good robustness, but the convergence efficiency and accuracy of alignment are contradictory, which is necessary to set appropriate control parameters to reconcile. Because Kalman alignment method is based on a deterministic filtering model, the algorithm is relatively stable, but the drift of IMU (Inertial Measurement Unit) will cause the drift of the errors of misalignment angles. In order to take into account the effects of both long and short damping periods on compass alignment, the exponential finite time-varying damping period is used to improve the convergence efficiency of azimuth alignment. In order to solve the divergence of horizontal misalignment angles of Kalman precise alignment algorithm, a realtime correction algorithm of attitude matrix with full feedback of misalignment angle estimations is introduced. The simulation and turntable experiments verify the effectiveness of the improved methods.

In Situ Magnetic Alignment and Cross-Linking of Injectable Microparticles into Centimeter-Scale Fibers for Efficient Myoblast Alignment and in Vivo Fiber Formation

Muscle cell alignment plays an essential key role in the development of parallelly organized myotubes and the exertion of mechanical functions. Despite remarkable advances in cell alignment, there is still a need for a simpler and more efficient method of stably aligning and supporting cells. Here, we propose magnetic assembly of alginate-coated magnetic microparticles for myoblast alignment. Applying an external magnetic field in a controlled manner followed by ionic cross-linking of adjacent alginate chains led to the formation of stable linear alignment of particles in centimeter-scale even after the removal of the magnetic field. Based on this anisotropic alignment of bundles consisting of magnetic particles with further modification of alginate with arginine–glycine–aspartic acid, myoblast alignment was successfully demonstrated in vitro. Moreover, these particles can be simply injected through a needle without extra surgery and magnetically assembled to maintain the aligned structure in vivo. This i...

HLA*LA-HLA typing from linearly projected graph alignments.

SummaryHLA*LA implements a new graph alignment model for human leukocyte antigen (HLA) type inference, based on the projection of linear alignments onto a variation graph. It enables accurate HLA type inference from whole-genome (99% accuracy) and whole-exome (93% accuracy) Illumina data; from long-read Oxford Nanopore and Pacific Biosciences data (98% accuracy for whole-genome and targeted data) and from genome assemblies. Computational requirements for a typical sample vary between 0.7 and 14 CPU hours per sample.Availability and implementationHLA*LA is implemented in C++ and Perl and freely available as a bioconda package or from https://github.com/DiltheyLab/HLA-LA (GPL v3).Supplementary information Supplementary data are available at Bioinformatics online.

Environmental dependence of ellipticity correlation functions of intrinsic alignments

In this work we investigate the environmental dependence of the intrinsic ellipticity correlations in cosmic shear surveys. We use the quadratic and linear alignment model to describe the contributions by spiral and elliptical galaxies, respectively. The density field is in both cases described by a Gaussian random field and ellipticity correlation functions that are conditional on the environment of the galaxies are constructed by sampling random values for the tidal tensor and inertial tensor. The covariance of the Gaussian random process from which the tensor entries are drawn is decomposed by means of a spherical Fourier-Bessel transformation of the density field. The dependence on environment is modelled by the number of positive eigenvalues of the tidal tensor, which allows a differentiation between voids, sheets, filaments and superclusters. We find that elliptical galaxies align strongest in elongated structures such as sheets and filaments with an amplitude almost an order of magnitude higher compared to the alignment in clusters or voids. In contrast to this, spiral galaxies align equally strong in all environments. Cross-alignments between different environments are smaller than the respective auto-correlations subject to the Cauchy-Schwarz inequality which is an effective bound on their amplitude. Furthermore, we find misalignment between inertial and tidal tensor to be stronger in anisotropic regions compared to clusters or voids. While the imprint of weak lensing on galaxy ellipticities is agnostic about the environment, using environment information can help to distinguish between lensing and the intrinsic alignment signal.

Nonparametric cosmology with cosmic shear

We present a method to measure the growth of structure and the background geometry of the Universe -- with no a priori assumption about the underlying cosmological model. Using Canada-France-Hawaii Lensing Survey (CFHTLenS) shear data we simultaneously reconstruct the lensing amplitude, the linear intrinsic alignment amplitude, the redshift evolving matter power spectrum, P(k,z), and the co-moving distance, r(z). We find that lensing predominately constrains a single global power spectrum amplitude and several co-moving distance bins. Our approach can localise precise scales and redshifts where Lambda-Cold Dark Matter (LCDM) fails -- if any. We find that below z = 0.4, the measured co-moving distance r (z) is higher than that expected from the Planck LCDM cosmology by ~1.5 sigma, while at higher redshifts, our reconstruction is fully consistent. To validate our reconstruction, we compare LCDM parameter constraints from the standard cosmic shear likelihood analysis to those found by fitting to the non-parametric information and we find good agreement.

The dependence of intrinsic alignment of galaxies on wavelength using KiDS and GAMA

The outer regions of galaxies are more susceptible to the tidal interactions that lead to intrinsic alignments of galaxies. The resulting alignment signal may therefore depend on the passband if the colours of galaxies vary spatially. To quantify this, we measured the shapes of galaxies with spectroscopic redshifts from the GAMA survey using deep gri imaging data from the KiloDegree Survey. The performance of the moment-based shape measurement algorithm DEIMOS was assessed using dedicated image simulations, which showed that the ellipticities could be determined with an accuracy better than 1% in all bands. Additional tests for potential systematic errors did not reveal any issues. We measure a significant difference of the alignment signal between the g, r and i-band observations. This difference exceeds the amplitude of the linear alignment model on scales below 2 Mpc h−1. Separating the sample into central/satellite and red/blue galaxies, we find that the difference is dominated by red satellite galaxies.

Small-amplitude hunting diagnosis method for high-speed trains based on the bogie frame’s lateral–longitudinal–vertical data fusion, independent mode function reconstruction and linear local tangent space alignment

Hunting stability is an important factor that influences the running safety of high-speed trains. Most of the existing hunting monitoring methods monitor only the standard hunting. The small-amplitude hunting, however, not only affects ride comfort but also aggravates the wheel–rail wear. Therefore, to extend the service life of wheels and rails and to improve the ride comfort, it is extremely important to monitor the small-amplitude hunting. Hunting motion is a coupled movement of lateral and yaw displacements of the wheelset. When the bogie is in an unstable state, instability will occur not only in the lateral side but also in the longitudinal and vertical sides of the bogie. To improve the robustness of the small-amplitude hunting monitoring methods, this study proposes an idea of the bogie frame’s lateral–longitudinal–vertical data fusion. In addition, the small-amplitude hunting signals have strong nonlinear characteristics, and their frequency and amplitude are unstable. Using only the amplitude or frequency to detect the small-amplitude hunting has obvious shortcomings. Therefore, a new feature extraction method based on the independent mode function reconstruction and linear local tangent space alignment (IMFR-LLTSA) is proposed. This method has been tested with three simulated signals. Finally, a method of combining the bogie frame’s lateral–longitudinal–vertical data fusion and IMFR-LLTSA is used to identify the small-amplitude hunting of high-speed trains. This method has been validated using the data of the CRH380a high-speed train running on the Shanghai–Hangzhou line, monitored by the authors’ research group. The results show that this method is superior to the single lateral diagnosis method.

Study on Planetary Gear Degradation State Recognition Method Based on the Features With Multiple Perspectives and LLTSA

Planetary gear is an important part of the transmission system of large electromechanical equipment. Therefore, it is very important to monitor the degradation of the state of the planetary gear. A method for the degradation state recognition of planetary gear based on the features with multiple perspectives and linear local tangent space alignment (LLTSA) algorithm is presented. First, the time domain features of the original vibration signal are extracted, which have the statistical properties and global significance. Then, the detailed features which pay more attention to the detailed information of the vibration signal are extracted on the basis of improved complete ensemble empirical mode decomposition with adaptive noise, and all those features constitute high dimensional original features. In order to solve the problems of information redundancy and interference features, the original features are processed by LLTSA, and the extraction of low dimensional sensitive features can be achieved. Finally, the optimized support vector machine is studied to recognize the low dimensional sensitive features. The result shows that the proposed method can recognize different degradation states of planetary gear accurately and effectively.

Pathogen-Host Analysis Tool (PHAT): an integrative platform to analyze next-generation sequencing data.

The Pathogen-Host Analysis Tool (PHAT) is an application for processing and analyzing next-generation sequencing (NGS) data as it relates to relationships between pathogens and their hosts. Unlike custom scripts and tedious pipeline programming, PHAT provides an integrative platform encompassing raw and aligned sequence and reference file input, quality control (QC) reporting, alignment and variant calling, linear and circular alignment viewing, and graphical and tabular output. This novel tool aims to be user-friendly for life scientists studying diverse pathogen-host relationships. The project is available on GitHub (https://github.com/chgibb/PHAT) and includes convenient installers, as well as portable and source versions, for both Windows and Linux (Debian and RedHat). Up-to-date documentation for PHAT, including user guides and development notes, can be found at https://chgibb.github.io/PHATDocs/. We encourage users and developers to provide feedback (error reporting, suggestions and comments).

Algorithmic Beamforming Design for MIMO Multiway Relay Channel With Clustered Full Data Exchange

This paper studies the beamforming design for the multiple-input multiple-output (MIMO) multiway relay channel with clustered full data exchange. We formulate the linear signal alignment in the model under a rank-constrained rank-minimization (RCRM) framework. Our contribution is twofold. We decompose the RCRM problem into independent rank-minimization subproblems and put forth an iterative algorithm for the beamforming design. For symmetric antenna setups, our approach advances the state of the art by expanding the achievable degree of freedom (DoF) region, and for asymmetric antenna setups, our approach can be directly applied while prior approaches are not readily applicable.

Non-destructive identification of maize haploid seeds using nonlinear analysis method based on their near-infrared spectra

The identification of maize haploid seeds is a significant process in genetic research and modern maize breeding. Adopting near-infrared spectroscopy technology to distinguish haploid seeds from hybrid seeds has the advantages of being non-destructive, rapid and low cost. However, due to the influence of light, temperature, humidity, near-infrared intensity, instrument and dynamic change of seed activity, the near-infrared spectra of maize seeds showed high dimensional nonlinear characteristics. In this study, to make full use of the class label information, a nonlinear feature analytical method for haploid maize seeds identification based on Supervised Virtual Sample Kernel Locality Preserving Projection (SVSKLPP) has been proposed. The experimental results showed that the nonlinear identification model SVSKLPP achieved strong classification performance to identify the maize haploid seeds. Moreover, compared with the linear feature extraction methods Principal Component Analysis, Orthogonal Linear Discriminant Analysis, Locality Preserving Projection, Supervised Virtual Sample Locality Preserving Projection and nonlinear feature extraction methods Kernel Locality Preserving Projection, Isomap, Locally Linear Embedding, Laplacian Eigenmaps and Local Tangent Space Alignment, the SVSKLPP model achieved a better performance. The average accuracy, sensitivity and specificity using method SVSKLPP were 97.1%, 98.8% and 95.4% respectively, and it also had high robustness. The overall results show that the SVSKLPP-NIR methodology was efficient in accurately identifying haploid maize seeds, thus demonstrating its capabilities for application in haploid breeding for crop variety improvement.

Linearly aligned single-chiral vortices in hexagonal manganites by insitu electric arc heating

Nanoscale topological defects, such as vortices and skyrmions in ferroic systems, have been intensively investigated due to their intriguing properties and behaviors. In addition to harnessing and tuning their functionalities, spatial manipulation and control of topological defects as functional elements are important for future nanotechnologies. Here, we report a linear alignment behavior of single-chiral vortices observed in thin transmission electron microscopy samples of multiferroic hexagonal manganites during an in situ heating experiment. In order to avoid chemical degradation during high-temperature heating in vacuum, we have utilized a rapid heating and quenching by $in$ situ electric arcing. Using atomic resolution electron microscopy and phase-field simulation, we found that vortices and antivortices formed near the phase transition temperature are pulled out in the opposite directions by mechanical strain to leave single-chiral vortices linearly aligned along an isothermal line formed during quenching. Our study provides important insight into spatial manipulation of the topological defects in oxide multiferroics by investigating far-equilibrium dynamics of symmetry-breaking continuous phase transitions.

Middle Bronze Age societies and barrow line chronology. A case study from the Bukivna ‘necropolis’, Upper Dniester Basin, Ukraine

The area of the Upper Dniester Basin in Western Ukraine comprises one of the largest concentrations of barrows with the exception of the steppe zone. This article concerns the absolute chronology of one mound group in Bukivna, built in the Middle Bronze Age by the people of the Komarów culture. It also focuses on reconstructing the spatial arrangement of barrows and explaining the creation of their specific linear alignment. A Bayesian statistical analysis of radiocarbon AMS dates collected from five excavated tumuli revealed the chronological and spatial organization of the Bukivna barrows. Moreover, a seriation and correspondence analysis was performed on pottery from the barrows to expose the chronology of specific ornamentation groups. This research allowed for the scenario of the emergence of mounds in the first half of the 2nd millennium BC to be reconstructed. In light of the presented data, it is theorized that barrows were arranged in linear alignments along selected hill zones, although they did not necessarily proceed in a continuous or defined direction. Structuring of the funerary space resulted from the extension of mound groups, which probably represent family sub-necropolises. Linear arrangements of mounds were derived by merging the particular groups; barrows were erected in areas apart from the ‘planned’ structure, usually during different periods (but sometimes simultaneously). It was only after some time that the final alignment formation was accomplished, thus ending the process of structuring particular fragments of the barrow landscape.