GraphChainer: Co-linear Chaining for Accurate Alignment of Long Reads to Variation Graphs

Aligning reads to a variation graph is a standard task in pangenomics, with downstream applications in e.g., improving variant calling. While the vg toolkit (Garrison et al., Nature Biotechnology, 2018) is a popular aligner of short reads, GraphAligner (Rautiainen and Marschall, Genome Biology, 2020) is the state-of-the-art aligner of long reads. GraphAligner works by finding candidate read occurrences based on individually extending the best seeds of the read in the variation graph. However, a more principled approach recognized in the community is to co-linearly chain multiple seeds. We present a new algorithm to co-linearly chain a set of seeds in an acyclic variation graph, together with the first efficient implementation of such a co-linear chaining algorithm into a new aligner of long reads to variation graphs, GraphChainer. Compared to GraphAligner, at a normalized edit distance threshold of 40%, it aligns 9% to 12% more reads, and 15% to 19% more total read length, on real PacBio reads from human chromosomes 1 and 22. On both simulated and real data, GraphChainer aligns between 97% and 99% of all reads, and of total read length. At the more stringent normalized edit distance threshold of 30%, GraphChainer aligns up to 29% more total real read length than GraphAligner. GraphChainer is freely available at https://github.com/algbio/GraphChainer

Minimizing uncertainty in complete automation of Douglas-Peucker Algorithm for geospatial mapping

It is qualitatively evident that the greater the map scale change, the greater the optimal distance threshold of the Douglas-Peucker Algorithm, which is used in polyline simplification. However, no specific quantitative relationships between them are known by far, causing uncertainties in complete automation of the algorithm. To fill this gap, the current paper constructs quantitative relationships based on the spatial similarity theories of polylines. A quantitative spatial similarity relationship model was proposed and evaluated by setting two groups of control experiments and taking <C, T> as coordinates. In order to realize the automatic generalization of the polyline, we verified whether these quantitative relationships could be fitted using the same function with the same coefficients. The experiments revealed that the unary quadratic function is the best, whether the polylines were derived from different or the same geographical feature area(s). The results also show that using the same optimal distance threshold is unreasonable to simplify all polylines from different geographical feature areas. On the other hand, the same geographical feature area polylines could be simplified using the same optimal distance threshold. The uncertainties were assessed by evaluating the automated generalization results for position and geometric accuracy perspectives using polylines from the same geographic feature areas. It is demonstrated that in addition to maintaining the geographical features, the proposed model maintains the shape characteristics of polylines. Limiting the uncertainties would support the realization of completely automatic generalization of polylines and the construction of vector map geodatabases.

Building Plane Segmentation Based on Point Clouds

Planes are essential features to describe the shapes of buildings. The segmentation of a plane is significant when reconstructing a building in three dimensions. However, there is a concern about the accuracy in segmenting plane from point cloud data. The objective of this paper was to develop an effective segmentation algorithm for building planes that combines the region growing algorithm with the distance algorithm based on boundary points. The method was tested on point cloud data from a cottage and pantry as scanned using a Faro Focus 3D laser range scanner and Matterport Camera, respectively. A coarse extraction of the building plane was obtained from the region growing algorithm. The coplanar points where two planes intersect were obtained from the distance algorithm. The building plane’s optimal segmentation was then obtained by combining the coarse extraction plane points and the corresponding coplanar points. The results show that the proposed method successfully segmented the plane points of the cottage and pantry. The optimal distance thresholds using the proposed method from the uncoarse extraction plane points to each plane boundary point of cottage and pantry were 0.025 m and 0.030 m, respectively. The highest correct rate and the highest error rate of the cottage’s (pantry’s) plane segmentations using the proposed method under the optimal distance threshold were 99.93% and 2.30% (98.55% and 2.44%), respectively. The F1 score value of the cottage’s and pantry’s plane segmentations using the proposed method under the optimal distance threshold reached 97.56% and 95.75%, respectively. This method can segment different objects on the same plane, while the random sample consensus (RANSAC) algorithm causes the plane to become over-segmented. The proposed method can also extract the coplanar points at the intersection of two planes, which cannot be separated using the region growing algorithm. Although the RANSAC-RG method combining the RANSAC algorithm and the region growing algorithm can optimize the segmentation results of the RANSAC (region growing) algorithm and has little difference in segmentation effect (especially for cottage data) with the proposed method, the method still loses coplanar points at some intersection of the two planes.

Special Vehicles to Prevent Touching High-voltage Lines Monitoring and Warning Device

Domestic regional special vehicles and construction personnel high-voltage electrocution accidents always occur, resulting in large-scale equipment and socio-economic losses. Based on this, in order to effectively reduce special vehicles touching high-voltage lines causing safety accidents, this paper researches and designs a safety monitoring and warning device for special vehicles touching high-voltage lines, mainly including sensor monitoring templates, signal transmission templates and monitoring and warning alert templates, through the decoding of different template principles, combined with electric field induction and wireless transmission principles, the safety distance of high-voltage lines is relevant to explore, then when Special vehicle objects into the safety distance threshold, that is, to start the information monitoring alarm, to remind the construction of special vehicle equipment and personnel away from electrocution, to ensure safe production. Through the monitoring and warning device, the rationalization, economy and safety of high-voltage line can be achieved.

Measuring area-level disadvantage in Australia: development of a locally sensitive indicator

Background In Australia, the Socio-Economic Indexes for Areas (SEIFA), which includes the Index of Relative Socioeconomic Disadvantage (IRSD), captures the socioeconomic characteristics of areas. Because SEIFA rankings are relative to the country or state, the decile categorisations may not reflect an area’s socioeconomic standing relative to areas nearby. Aims The aim of the research was to explore whether IRSD rankings could be re-ranked to become locally sensitive. Data and methods Using existing SEIFA data to redistribute the membership of current decile IRSD groups, we tested three methods to re-rank all SA1 areas relative to the nearest areas capped at: (1) the nearest 99 neighbours, (2) a population threshold of 50,000 (3) a distance threshold of 10 km. Results The reclassification of SEIFA IRSD deciles was largest (up to 8 decile points of change) when comparing the nearest neighbour and population threshold local methods to current state-based rankings. Moreover, compared to using current national and state SEIFA IRSD rankings, the use of local rankings resulted in more evenly distributed deciles between cities, regional, and remote areas. Conclusions Because SEIFA IRSD rankings are used to allocate resources and health services, we encourage the combined use of a state and local ranking to refine areas considered the most disadvantaged.

Abstract 1122‐000075: Optimization of Transport Protocols to Increase the Odds of Thrombectomy

Introduction : We sought to determine a distance threshold where mode of transportation impacted treatment options for potential thrombectomy patients. Methods : We retrospectively reviewed transferred stroke patients to our comprehensive stroke center within 8 hours of onset from January 2017 to December 2019. In our analysis, all patients had a CTA confirmed large vessel occlusion, NIHSS >10 and arrived within 8 hours of onset as a candidate for thrombectomy. Patients were not treated with thrombectomy if they presented with a completed infarct or hemorrhagic conversion. Patients were transferred by air or ground based on availability and safety. Transfers were grouped based on distance: 0–30 miles, 31–60 miles, 61–90 and > 90 miles. We performed a binomial logistic regression for each distance group to determine a threshold where the odds of receiving thrombectomy statistically decoupled based on mode of transportation. Results : Of the 243 patients reviewed, 52.1% (126) received thrombectomy. Transport for 50.8% (123) patients was by air. Hospitals transferring within 0–30 miles accounted for 26.6% (65); 31–60 miles accounted for 22.1% (54); 61–90 miles accounted for25.8% (63) and >90 miles accounted for 24.8% (60). The odds of receiving a thrombectomy were significantly higher with air transportation (OR 3.0, CI 1.04‐8.74, p = 0.043) at a distance threshold of >90 miles. At a distance threshold of 10 to 30 miles, the odds of receiving a thrombectomy were significantly higher with ground transportation (OR 5.5, CI 1.15‐26.14, p = 0.032). There was no difference between modes of transportation for 31 to 90 miles. Conclusions : Our analysis suggests that air transport beyond 90 miles increases the odds of receiving a thrombectomy for patients arriving within 8 hours of symptom onset. Ground transport, rather than air transport, between 10 and 30 miles may be more beneficial. Our results suggest that specific regional transport thresholds based on distance do exist and if recognized and altered can result in more favorable transfers.

Identifying the Development Potential for Urban Integration Based on Transport Accessibility—The Case for Northeast China

Urban integration, a new concept in urban and regional research, is an inevitable outcome of urban development. Based on accessibility analysis, this study uses urban and road network data to identify urban pairs in Northeast China which meet the distance threshold for urban integration and establishes an index system to evaluate the development potential. The research shows that in Northeast China, the results for urban integration are similar to those for the present urban structure in China, that is, a spatial pattern with provincial capital cities at the core and an urban belt as the axis. According to the evaluation, areas with potential for urban integration may be classified into four categories, namely, dominant areas, key areas, ordinary areas, and alternative areas. The candidate and potential areas for urban integration tend to be concentrated near a provincial capital city or a regional development zone. The results show that the development potential for urban integration varies greatly among the different urban pairs and the main constraining factors are different for each location. Among the constraining factors, the commuting time, costs, and economic conditions for the citizens are the most important.

Enlightening the black and white: species delimitation and UNITE species hypothesis testing in the Russula albonigra species complex

ABSTRACTRussula albonigra is considered a well-known species, morphologically delimited by the context of the basidiomata blackening without intermediate reddening, and the menthol-cooling taste of the lamellae. It is supposed to have a broad ecological range and a large distribution area. A thorough molecular analysis based on four nuclear markers (ITS, LSU, RPB2 and TEF1-α) shows this traditional concept of R. albonigra s. lat. represents a species complex consisting of at least five European, three North American, and one Chinese species. Morphological study shows traditional characters used to delimit R. albonigra are not always reliable. Therefore, a new delimitation of the R. albonigra complex is proposed and a key to the described European species of R. subgen. Compactae is presented. A lectotype and an epitype are designated for R. albonigra and three new European species are described: R. ambusta, R. nigrifacta, and R. ustulata. Different thresholds of UNITE species hypotheses were tested against the taxonomic data. The distance threshold of 0.5% gives a perfect match to the phylogenetically defined species within the R. albonigra complex. Publicly available sequence data can contribute to species delimitation and increase our knowledge on ecology and distribution, but the pitfalls are short and low quality sequences.

Similar Supergraph Search Based on Graph Edit Distance

Subgraph and supergraph search methods are promising techniques for the development of new drugs. For example, the chemical structure of favipiravir—an antiviral treatment for influenza—resembles the structure of some components of RNA. Represented as graphs, such compounds are similar to a subgraph of favipiravir. However, the existing supergraph search methods can only discover compounds that match exactly. We propose a novel problem, called similar supergraph search, and design an efficient algorithm to solve it. The problem is to identify all graphs in a database that are similar to any subgraph of a query graph, where similarity is defined as edit distance. Our algorithm represents the set of candidate subgraphs by a code tree, which it uses to efficiently compute edit distance. With a distance threshold of zero, our algorithm is equivalent to an existing efficient algorithm for exact supergraph search. Our experiments show that the computation time increased exponentially as the distance threshold increased, but increased sublinearly with the number of graphs in the database.

Social Distance Monitoring Using Drone

Within the present times, the priority and danger of the COVID-19 virus still stand large. Manual looking of social distancing norms is impractical with associate in nursing oversized population moving concerning and with the short task force and resources to administer them. There is a want for a light-weight, robust, and 24*7 video-monitoring system that automates this technique. This paper proposes a comprehensive and effective resolution to perform person detection and social distancing violation detection exploitation object detection, agglomeration and Convolution Neural Network (CNN) based binary classifier. The framework uses the Scaled-YOLOv4 seeing paradigm to identify humans in video sequences. The detection formula uses a pre-trained formula that's connected to an additional trained layer using a frontal human information set. The detection model identifies peoples exploitation detected bounding box information. Exploitation the mathematician distance, the detected bounding box centroid’s pairwise distances of individuals unit determined. A threshold is used to estimate the social distance violations between people. Here, we have a tendency to tend to use Associate in nursing approximation of physical distance to pixel to line the sting price. A violation threshold is established to live whether or not the gap price breaches the minimum social distance threshold. To boot, a trailing formula is employed to sight individuals in video sequences such the one that violates/ crosses the social distance threshold is, additionally, being half-track. Experiments unit administered on whole completely different video sequences to ascertain the efficiency of the model. Findings indicate that the developed framework successfully distinguishes individuals UN agency walk too about to and breach/violate social distances.