Vertical Edges Research Articles

A Neutron Diffraction Study of the Effect Produced by the Direction of Crystal Growth on the Distribution of Residual Stresses in Austenite Steel Prisms Manufactured by Selective Laser Melting

The effect affected by the choice of the direction of the crystal growth by selective laser melting on the distribution of residual stresses was studied on the example of initiated growing of a 20 × 20 × 70-mm prism of steel 316L. Prisms with different growth directions (along their long and short edges) have been investigated. Neutron stress diffractometry providing the measurement of all three stress tensor components in massive materials and products by a nondestructive method was used. Compressive stresses are formed in the central part of a prism in both cases. They are close to zero or transit to tensile stresses when approaching the surface. In the prism grown vertically along the long edge, tensile stresses are higher and occupy a larger volume as compared to the prism grown along the short edge. Maximum tensile stresses (~500 MPa) near the vertical prism edges are close to the ultimate yield strength of the material (~540 MPa). The maximum compressive stresses (~–400 MPa) are formed in the central part of the vertical prism.

HFENet: A lightweight hand‐crafted feature enhanced CNN for ceramic tile surface defect detection

Inkjet printing technology can make tiles with very rich and realistic patterns, so it is widely adopted in the ceramic industry. However, the frequent nozzle blockage and inconsistent inkjet volume by inkjet printing devices, usually leads to defects such as stayguy and color blocks in the tile surface. Especially, the stayguy in complex pattern is difficult to identify by naked eyes due to it is easily covered by complex patterns and becomes invisible, this brings great challenge to tile quality inspection. Nowadays, the machine learning is employed to address the issues. The existing machine learning methods based on hand-crafted features are capable of stayguy detection of the tiles with a simple pattern, but not applicable for complex patterns due to the interference of pattern in feature extraction. The emerging deep-learning-based methods have the potential to be applied for stayguy detection with complex patterns, but cannot achieve real-time detection due to high complexity. In this paper, a lightweight hand-crafted feature enhanced convolutional neural network (named HFENet) is proposed for rapid defect detection of tile surface. First, we perform data enhancement on the original image by global histogram equalization and image addition. Second, for the special shape of stayguy which is usually vertical, we embed the extended vertical edge detection operator (Prewitt) as convolution kernel into HFENet to extract the hand-crafted vertical edge features of the test image and eliminate the interference of complex pattern in the feature extraction. Third, the 5 × 1 asymmetric convolution kernel with a dilation rate of 2 is used to improve the utilization of convolution kernel and reduce the complexity of the model. Fourth, to reach the real-time requirements, a memory access cost-aware design is proposed, which can orchestrate the number of shallow convolution layers and deep convolution layers in feature extraction. The experiments were performed on the ceramic tile image data set captured by high-resolution industrial cameras in ceramic tile production line. Experimental results show that the HFENet outperforms the state-of-the-art semantic segmentation networks (i.e., UNet, FCN-8s, SegNet, DeepLabV3+, etc.) and lightweight networks (i.e., ShuffleNet, MobileNet, and SqueezeNet). All the code and data are available at a GitHub repository (https://github.com/RobotvisionLab/HFENet).

Non-linear Embedding Methods for Identifying Similar Brain Activity in 1 Million iEEG Records Captured From 256 RNS System Patients.

Finding electrophysiological features that are similar across patients with epilepsy may facilitate identifying treatment options for one patient that worked in patients with similar brain activity patterns. Three non-linear iEEG (intracranial electroencephalogram) embedding methods of finding similar cross-patient iEEG records in a large iEEG dataset were developed and compared. About 1 million iEEG records from 256 patients with drug-resistant focal onset seizures who were treated in prospective trials of the RNS System were used for analyses. Data from 200, 25, and 31 patients were randomly selected to be in the train, validation, and test datasets. In method 1, ResNet50 convolutional neural network (CNN) model pre-trained on the ImageNet dataset was used for extracting feature maps from spectrogram images (ImageNet-ResNet) of iEEG records. In method 2, ResNet50 custom trained on an iEEG classification task using ~138,000 manually labeled iEEG records was used as the feature extractor (ESC-ResNet). Feature maps were passed through dimensionality reduction and k nearest neighbors were found in the reduced feature space. In method 3, a 256 dimensional iEEG embedding space was learned via contrastive learning by training a ResNet50 model with triplet training sets generated using within-patient iEEG clustering (CL-ResNet). All three methods had comparable performance when identifying iEEG records from the search dataset similar to test iEEG records of baseline (non-seizure) and interictal spiking activity. Epileptic interictal spikes are represented by vertical (broadband) edges in spectrogram images, and hence even generic features extracted using models trained on everyday images appear to be sufficient to represent iEEG records with similar levels of interictal spiking activity in close proximity. In the case of electrographic seizures, however, the ESC-ResNet model, identified cross-patient iEEG records with electrographic seizure morphology features that were most similar to the test iEEG records. For nuanced electrographic seizure iEEG representation learning, domain specific model training with manually generated labels had the advantage. Finally, representative iEEG records were selected from every patient using an unsupervised clustering method which effectively reduced the number of iEEG records in the search dataset from ~750,000 to 2,148, thus substantially reducing the time required for finding similar cross-patient iEEG records.

Simulations of Luminescent Solar Concentrator Bifacial Photovoltaic Mosaic Devices Containing Four Different Organic Luminophores

In this article, various design configurations of luminescent solar concentrator photovoltaic (LSC-PV) devices have been simulated using Monte Carlo raytracing. These LSC PV devices are composed of mono-crystalline silicon solar cells and cubical poly (methyl methacrylate) lightguides, each containing one of the following dyes: Lumogen F Red 305, Lumogen F Orange 240, Perylene Green, or Perylene-diimide di-tert-butylphenyl, which results in different device colors. In these devices, mono-crystalline silicon bifacial PV cell are placed in between the vertical edge(s) of neighboring cubical lightguides whereas monofacial PV cells are positioned at the bottom of a lightguide. Each device is made out of five cubical 10 × 10 × 10 mm³ lightguides, meaning that the PV cells measure 10 × 10 mm². The main research goal of this article is to evaluate the optical and electrical performance of five of such configured LSC-PV devices. Hence, the spectral distribution of irradiance received by the edges and bottom of the devices has been simulated as well as the optical efficiency of these surfaces and the power conversion efficiency of each device. The theoretical results for power conversion efficiency are in the range of 13.3% to 18% under irradiance of 1000 W/m² and depend on the dyes applied. Hence, this article demonstrates the potential for energy generation by these colorful LSC-PV technologies, which we have called Mosaic devices.

The contribution of Antarctic moss peat to the understanding of global peatland processes

AbstractThe moss banks of the Maritime Antarctic composed of one or both of the mosses Chorisodontium aciphyllum and Polytrichum strictum form peat banks up to 3.4 m thick and 5500 years of age. They represent perhaps the simplest peat-forming systems in the world, so studying their dynamics can help in the understanding of peatland dynamics generally, particularly those of temperate blanket peat. They can provide insights into how the balance of growth, decomposition and compaction of peat results in peat formation, how downhill creep can be the cause of both vertical edges and the creation of patterned bogs and how erosion of peat can be a natural process.

Research on Vehicle Detection and Recognition Based on Infrared Image and Feature Extraction

Vehicle detection and identification and safe distance keeping technology have become the main content of current intelligent transportation system research. Among them, vehicle detection and recognition is one of the most important research contents, and it is also crucial to the safe driving of vehicles. Real-time detection and recognition of current vehicles can effectively prevent the occurrence of malignant traffic accidents such as rear-end collision. Because the infrared image has some shortcomings such as poor contrast, loud noise, and blurred edge, this paper mainly studies the color space preprocessing of the image and uses threshold segmentation method and infrared image enhancement to segment the front vehicle and background. That is to say, by analyzing the infrared image captured by infrared CCD, we use median filter to remove noise from the collected infrared image and then use the improved histogram equalization to enhance the contrast of the image. Vertical Sobel operator is selected to enhance the vertical edge of the image, and the image is segmented by binary segmentation method. Finally, vehicle detection and recognition are realized by vertical edge symmetry, aspect ratio, and gray-scale symmetry. The experimental image and experimental data analysis results show that the image processing technology studied in this paper has achieved the intended research purpose.

Automated visual surveying of vehicle heights to help measure the risk of overheight collisions using deep learning and view geometry

AbstractOverheight vehicle collisions continuously pose a serious threat to transportation infrastructure and public safety. This study proposed a vision‐based method for automatic vehicle height measurement using deep learning and view geometry. In this method, vehicle instances are first segmented from traffic surveillance video frames by exploiting mask region‐based convolutional neural network (Mask R‐CNN). Then, 3D bounding box on each vehicle instance is constructed using the obtained vehicle silhouette and three orthogonal vanishing points in the surveilled traffic scene. By doing so, the vertical edges of the constructed 3D bounding box are directly associated with the vehicle image height. Last, the vehicle's physical height is computed by referencing an object with a known height in the traffic scene using single view metrology. A field experiment was performed to evaluate the performance of the proposed method, leading to the mean and maximum errors of 3.6 and 6.6, 5.8 and 12.9, 4.4 and 8.1, and 9.2 and 18.5 cm for cars, buses, vans, and trucks, respectively. The experiment also demonstrated the ability of the method to overcome vehicle occlusion, shadow, and irregular appearance interferences in height estimation suffered by existing image‐based methods. The results signified the potential of the proposed method for overheight vehicle detection and collision warning in real traffic settings.

Spatio-temporal combinatorics of resource flows conservation and reduction of risks in conditions of uncertainty of the external environment

Management of non-structured and weakly structured systems for the impacts of the dy-namic changes is not have a developed methodological basis. Management decisions are made on the basis of stochastic recommendations based on the results of existing experience with ex-trapolation to future trends without taking into account risks and possible faults. It is not neces-sary to introduce a great lack of value and inadequacy of acceptance of solutions, related to a wide range of criteria for assessments, without a wide range of factors, and highly direct indicators. When modeling management in the conditions of uncertainties of the environment, which are constantly changing, a large variety of source data is possible. The development of methods and models to support decision-making in terms of geo-graphically distributed processes is a very complex and non-trivial task. All interactions take place within a territorially distributed system. Such model can be built on a continuous basis, but it cannot be used to analyze spatial areas in real time. To reduce the level of risk and the results of possible losses, it is necessary to carefully study the possible carriers of risk, taking into account their individual characteristics, as well as market participants with the development of their original methods of risk management. The initial information on identifying problems of unstable market development is contained in the ratio of internal and external destabilizing factors. Information as an integral part of doing business plays a key role in reducing the risks that ensure the commercialization of proposals. Decision-making in a complex system is that from the available set of acceptable con-trols, it is necessary to identify several options that are the best. The rule that establishes the advantage in many solutions is the principle of optimality. When solving problems of optimal control as a set of valid alternatives use the combinatorics of acceptable management. An important difference between the construction of mathematical models of complex systems is that the modeling is not above the global function and the allocation of the main parts, and below, with the construction of models of individual processes and lower hierar-chical levels. Larger modules and the system as a whole are modeled on the basis of reasona-ble complexity. Combinatorics is directly related to simulation modeling, when it is impossible to apply mathematical solutions to problems in conditions of uncertainty. A perspective area of analysis and management of development under conditions of un-certainty and ambiguity of the external environment is graph theory using the Ford-Falkerson algorithm. Control under the action of constantly changing environments with the onset of change is solved using the Ford-Falkerson algorithm. The network of possible movements is considered as a connected digraph. In the conditions of global risks it is not necessary to count only on one direction of de-velopment. The sudden emergence of restrictions forces to move to another branch of the network, for which the network provides additional vertical edges with their probabilities and bandwidth. As the change of the situation is unpredictable, the transition from one branch to another can occur spontaneously, which is reflected in the presence in the source network of inclined edges that have their own direction and their own weights. The introduction of the method of transition from one branch of the oriented network to another at the time of termination of its implementation due to the unpredictable influence of environmental factors ensures the distribution of risks between the components. The use of combinatorics of the proposed options for interactions in the state space, their implementation at different moments of iterations, their application with the synchronization of flow throughput can reduce the risks arising from the functioning of systems.

Individuals with autism show non-adaptive relative weighting of perceptual prior and sensory reliability.

Unique perceptual skills and abnormalities in perception have been extensively demonstrated in those with autism for many perceptual domains, accounting, at least in part, for some of the main symptoms. Several new hypotheses suggest that perceptual representations in autism are unrefined, appear less constrained by exposure and regularities of the environment, and rely more on actual concrete input. Consistent with these emerging views, a bottom-up, data-driven fashion of processing has been suggested to account for the atypical perception in autism. It is yet unclear, however, whether reduced effects of prior knowledge and top-down information, or rather reduced noise in the sensory input, account for the often-reported bottom-up mode of processing in autism. We show that neither is sufficiently supported. Instead, we demonstrate clear differences between autistics and neurotypicals in how incoming input is weighted against prior knowledge and experience in determining the final percept. Importantly, the findings tap central differences in perception between those with and without autism that are consistent across identified sub-clusters within each group.

A novel dual-loop ground-radiation antenna for circularly polarized GNSS applications

In this investigation, a circularly polarized (CP) dual-loop ground-radiation antenna has been proposed for GPS applications using a transverse loop and a longitudinal loop. The transverse loop is designed within an 8 mm × 4.5 mm (0.042λ × 0.024λ) clearance, installed at the horizontal edge of the ground plane for excitation of the ground mode along the y-axis, whereas a 1 mm × 10 mm (0.005λ × 0.053λ) longitudinal loop is etched at the vertical edge of the ground plane for excitation of the ground mode along the x-axis. In this way, the magnitudes and phases of the orthogonal components of the radiated electric field have been controlled independently, satisfying the CP conditions. The proposed antenna produced right-hand circular polarization towards the + z-axis, which has been verified using rectangular and square-shaped ground planes. Both simulation and measurement were conducted, and the measured axial ratio bandwidth with reference to 3 dB was 20 MHz (1.27%) while the impedance bandwidth with reference to −6 dB was 141 MHz (8.95%).

First-principles study on controlling transport gap of graphene nanoribbons using hybrid Armchair–Zigzag nanostructures

The electronic and transport properties of hybrid armchair–zigzag nanostructures, which include right-angles-shaped GNRs, U-shaped GNRs, and patterned nanopores structured GRNs, were studied by the combination of density functional theory and nonequilibrium Green’s function method. The density of state, electron transmission spectra, and molecular orbitals were analyzed. The obtained results show that right-angles-shaped GNRs junctions tend to open a transport gap when the numbers of right-angles are greater than or equal to 4. The gap increases insignificantly as the numbers of right-angles are greater than 4. It implies that the U-shaped GNR junction, corresponding to 4 right-angles structure, is a potential structure for controlling transport gap of GRNs. The transport gap of the U-shaped GNRs decreases as the length of horizontal edge increases. In contrast, the transport gap increases as the high of vertical edge increases. In addition, the patterned nanopore had an enormous influence on the electronic and transport properties though the armchair GNRs junctions, depending on the shape and size of nanopore. This research suggests that designed tailored GNRs based on hybrid armchair–zigzag nanostructures can be used to control the transport gap of graphene. The formation of quasi-bound states at zigzag edges of the hybrid nanostructures plays a key role.

Gravitational drainage on a vertical substrate of a narrow width

In this experimental study, by interferometry, we characterize the structure of a liquid film, draining due to gravity, on a vertical, narrow substrate. The surface tension effects affect the draining film from the two vertical edges, and eventually influence the shape over the entire width.

Critical points of Eisenstein series

For any even integer $k \ge 4$, let $\E_k$ be the normalized Eisenstein series of weight $k$ for $\SL_2(\Z)$. Also let $\D$ be the closure of the standard fundamental domain of the Poincar\'e upper half plane modulo $\SL_2(\Z)$. F.~K.~C.~Rankin and H. P. F. Swinnerton-Dyer showed that all zeros of $\E_k$ in $\D$ are of modulus one. In this article, we study the critical points of $\E_k$, that is to say the zeros of the derivative of $\E_k$. We show that they are simple. We count those belonging to $\D$, prove that they are located on the two vertical edges of $\D$ and produce explicit intervals that separate them. We then count those belonging to $\gamma\D$, for any $\gamma \in \SL_2(\Z)$.

An electrically small 4-port self-decoupled MIMO antenna pairs operating in n78 5G NR band for smartphone applications

In this article, a 4-port electrically small multiple-input multiple-output (MIMO) antenna system functioning in 5G n78 band for the future smartphone implementation is recommended. The system includes two antenna pairs that are positioned in the exact centers of the vertical edges of the smartphone system. The overall size of each antenna pair is only 23.5 × 5.2 mm2. The reduction is size is obtained by connecting the two radiators, and the antenna pair is excited by coaxial feeding technique. A very good and acceptable isolation amid the antenna elements are accomplished by inserting a T-shaped structure, and is further enhanced with the addition of a reflector at the backside of the radiator. The self-isolated MIMO system operates in the n78 sub-6 GHz band (3.4–3.6 GHz) of the 5G Frequency Range 1 (FR1), with worst case isolation of −17.5 dB between the antennas in the same block in the entire band of operation. The evolution analysis to acquire the proposed structure and parametric study of some ideal parameters are carried out to get a superior insight of the operating principle of the proposed structure. Various MIMO diversity parameters such as Envelope Correlation Coefficient (ECC), Channel Capacity Loss (CCL), Total Active Reflection Coefficient (TARC), Diversity Gain (DG), and Mean Effective Gain (MEG) of the MIMO system are measured and compared with the calculated values. The ECC value is <0.009 in the whole essential operating band, the poorest being between Ant.1 and Ant. 2. A model of the designed smartphone MIMO system is fabricated and experimentally verified, with acceptable coherence between the simulated and the measured results. The MIMO system has a total efficiency and peak gain over 74% and 4.53 dBi correspondingly in the complete operating bandwidth, making it a suitable contender for the future 5G smartphone application. Likewise, the effect of user hand on the S-Parameters and antenna pattern are studied and acceptable results are obtained. Also, the specific absorption rate of the system is analyzed, and <1.23 W/Kg is achieved.

Deformation and damage to buildings caused by ground movements in mining areas (case study)

Human activity causes transformations in the near-surface layers of the rock mass, which result in long-term impacts on buildings and engineering infrastructure. Mining activities are particularly disadvantageous in this context, as they trigger severe deformation processes that reach the soil surface as a result of the excavation of deposits. The prevention of accidents and disasters caused by these impacts is based on knowledge derived from observation. Therefore, the aim of this study was to acquire and update knowledge on the impact of mining-related ground deformation and tremors on buildings. The paper presents the results of measurements carried out on a group of buildings located in an underground mining area. The buildings have been affected by mining impacts since their construction in the 1980s. Despite the implementation of appropriate structural protection, the structures have been suffering deformation and damage. For the purposes of the study, two two-axis inclinometers were installed on the 15.2 m high bell tower, taking measurements at 6-hour intervals. Over a period of 10 months, changes in the leaning of the tower were measured and the condition of the other buildings observed.The study resulted in obtaining:&#x0D; &#x0D; values for the change in tilt of the two perpendicular walls of the tower (over a period of 10 months),&#x0D; correlation of the results with tremors measurements and periodic surveying measurements of the inclination of the vertical edge of the tower,&#x0D; image of damage to buildings caused by mining deformation of the ground.&#x0D; &#x0D; On the basis of an analysis of the location and timing of minefields excavation, the occurrence of real ground movement in the mining areas, continuing even after the end of mining works, was confirmed and irregular deformation of the originally perpendicular walls of the masonry tower building was demonstrated. The tower did not behave as a rigid body; its horizontal profile was deformed.

Carbon allotropes consisting of rings and cubes

Joint horizontal and vertical edges can hinge the polygonal carbon structures. Here, five carbon allotropes are proposed based on differently connected polygonal ring structures. Based on the number of rings from the basic units, the five carbon allotropes are termed 5M14, 6M16, 4-6M12, 4-6M6 and 4M-B12, respectively. The energetic, dynamical, mechanical and thermodynamic stabilities of five carbon allotropes are confirmed by energy, phonon dispersion, elastic constants, and ab initio molecular dynamics simulations. The calculated band structure and the density of states reveal that 5M14 and 4M-B12 are indirect band gap semiconductors with a band gap of 1.22 eV and 4.15 eV, respectively. While 6M16 exhibits semimetallic conductivity, 4-6M12 and 4-6M6 have metallic conductivity. These carbon allotropes may enrich the carbon family and facilitate the applications of carbon-based materials and promote the design of unique crystalline structures.

Full range I/II fracture behavior of asphalt mixtures containing RAP and rejuvenating agent using two different 3-point bend type configurations

In this study, a new test configuration was used to investigate the full range of mixed-mode I/II fracture behavior of asphalt mixtures using a Short Beam Bending (SBB) specimen with a vertical edge crack, which was subjected to an asymmetric three-point bending load. To evaluate the capabilities and assess the characteristics of this new specimen, the results of experiments were compared to Semi-Circular Bending (SCB) specimens. The materials used in this study were Stone Mastic Asphalt (SMA) mixtures containing various Reclaimed Asphalt Pavement (RAP) contents (0%, 30%, and 50%) with or without a rejuvenating agent additive. Results showed that pure Mode-I and pure mode-II fracture toughness values obtained from the SBB specimen were about 15% lower than fracture toughness obtained from the SCB specimens. Results also indicated that the addition of RAP materials into asphalt mixtures was improve the fracture toughness and fracture energy of asphalt mixtures. It can be inferred from the outcomes that the addition of 30% and 50% of RAP (with a rejuvenating agent) in asphalt mixtures increased the fracture toughness by roughly 20% and 30% in pure mode I and 15% and 25% in pure mode II, respectively. Besides, the rejuvenating agent also increased the fracture parameters values of RAP-contained asphalt mixtures in both sample types by an average of 10%. Moreover, a significant correlation between the fracture parameters of SCB and SBB specimens was observed.

Generation of filament winding patterns for elbows with various cross-sections

As a connecting component of tubes, the elbow is indispensable to pipe-fitting in composite products. Previous studies have addressed methods for generating winding paths based on parametric equations on the elbow. However, these methods are unsuitable for elbows whose surfaces are difficult to describe using mathematical expressions. In this study, a geometric method was proposed for generating winding patterns for various elbow types. With this method, the mandrel surface is first converted into uniform and high-quality quadrilateral elements; an algorithm is then provided for calculating the minimum winding angle for bridging-free. Next, an angle for non-bridging was defined as the design-winding angle to generate the uniform and slippage-free basic winding paths on the quadrilateral elements in non-geodesic directions. Finally, after a series of uniform points were calculated on the selected vertical edge according to the elbow type, the pattern paths were generated with the uniform points and basic paths. The proposed method is advantageously not limited to the elbow’s shape.

Fire resistance of external LSF walls with corrugated steel cladding

This paper presents the details of full-scale standard fire tests of external light-gauge steel-framed (LSF) walls with corrugated steel cladding exposed to fire on the external side. Corrugated steel cladding of 0.42mm thickness is generally used in roof and wall systems of buildings. In this study, it is used as the wall cladding of external LSF walls and as a lightweight cladding replacement to the combustible aluminium composite panels. A detailed investigation was undertaken to evaluate and understand the fire and energy performance of corrugated steel clad external LSF walls, which included (a) thermal property tests of two different types of Earthwool insulation (glass fibre insulation) used in wall systems, (b) full-scale (3m×3m) load bearing standard fire tests of two external LSF wall systems – first with cavity insulation and the second with external insulation and (c) THERM modelling of the tested walls. Steel cladding prevented direct exposure of fire on plasterboards and hence delayed the temperature rise and increased the failure time. Overlaps along the vertical edges of steel cladding played a critical role as gaps formed during the tests. The two external LSF wall systems achieved fire resistance levels (FRLs) in excess of two hours (122min and 158min) with improvements greater than 40% due to the addition of thin steel cladding. Replacing cavity insulation with external insulation improved the FRL by about 30% and also its effectiveness in terms of energy efficiency.

CoVizu: Rapid analysis and visualization of the global diversity of SARS-CoV-2 genomes.

Phylogenetics has played a pivotal role in the genomic epidemiology of severe acute respiratory syndrome coronavirus 2, such as tracking the emergence and global spread of variants and scientific communication. However, the rapid accumulation of genomic data from around the world-with over two million genomes currently available in the Global Initiative on Sharing All Influenza Data database-is testing the limits of standard phylogenetic methods. Here, we describe a new approach to rapidly analyze and visualize large numbers of SARS-CoV-2 genomes. Using Python, genomes are filtered for problematic sites, incomplete coverage, and excessive divergence from a strict molecular clock. All differences from the reference genome, including indels, are extracted using minimap2 and compactly stored as a set of features for each genome. For each Pango lineage (https://cov-lineages.org), we collapse genomes with identical features into 'variants', generate 100 bootstrap samples of the feature set union to generate weights, and compute the symmetric differences between the weighted feature sets for every pair of variants. The resulting distance matrices are used to generate neighbor-joining trees in RapidNJ that are converted into a majority-rule consensus tree for each lineage. Branches with support values below 50 per cent or mean lengths below 0.5 differences are collapsed, and tip labels on affected branches are mapped to internal nodes as directly sampled ancestral variants. Currently, we process about 2 million genomes in approximately 9 h on 52 cores. The resulting trees are visualized using the JavaScript framework D3.js as 'beadplots', in which variants are represented by horizontal line segments, annotated with beads representing samples by collection date. Variants are linked by vertical edges to represent branches in the consensus tree. These visualizations are published at https://filogeneti.ca/CoVizu. All source code was released under an MIT license at https://github.com/PoonLab/covizu.