Abstract

Human mobility across national borders is a key phenomenon of our time. At the global scale, however, we still know relatively little about the structure and nature of such transnational movements. This study uses a large dataset on monthly air passenger traffic between 239 countries worldwide from 2010 to 2018 to gain new insights into (a) mobility trends over time and (b) types of mobility. A time series decomposition is used to extract a trend and a seasonal component. The trend component permits—at a higher level of granularity than previous sources—to examine the development of mobility between countries and to test how it is affected by policy and infrastructural changes, economic developments, and violent conflict. The seasonal component allows, by measuring the lag between initial and return motion, to discern different types of mobility, from tourism to seasonal work migration. Moreover, the exact shape of seasonal mobility patterns is extracted, allowing to identify regular mobility peaks and nadirs throughout the year. The result is a unique classification of trends and types of mobility for a global set of country pairs. A range of implications and possible applications are discussed. Open-Access-Publikationsfonds 2019 Document type: Article

Abstract

Background: The massive amounts of data from next generation sequencing (NGS) methods pose various challenges with respect to data security, storage and metadata management. While there is a broad range of data analysis pipelines, these challenges remain largely unaddressed to date. Results: We describe the integration of the open-source metadata management system iRODS (Integrated Rule-Oriented Data System) with a cancer genome analysis pipeline in a high performance computing environment. The system allows for customized metadata attributes as well as fine-grained protection rules and is augmented by a user-friendly front-end for metadata input. This results in a robust, efficient end-to-end workflow under consideration of data security, central storage and unified metadata information. Conclusions: Integrating iRODS with an NGS data analysis pipeline is a suitable method for addressing the challenges of data security, storage and metadata management in NGS environments. Document type: Article

Abstract

Abstract"/p" "p"Background"/p" "p"In bioinformatics, it is important to build extensible and low-maintenance systems that are able to deal with the new tools and data formats that are constantly being developed. The traditional and simplest implementation of pipelines involves hardcoding the execution steps into programs or scripts. This approach can lead to problems when a pipeline is expanding because the incorporation of new tools is often error prone and time consuming. Current approaches to pipeline development such as workflow management systems focus on analysis tasks that are systematically repeated without significant changes in their course of execution, such as genome annotation. However, more dynamism on the pipeline composition is necessary when each execution requires a different combination of steps."/p" "p"Results"/p" "p"We propose a graph-based approach to implement extensible and low-maintenance pipelines that is suitable for pipeline applications with multiple functionalities that require different combinations of steps in each execution. Here pipelines are composed automatically by compiling a specialised set of tools on demand, depending on the functionality required, instead of specifying every sequence of tools in advance. We represent the connectivity of pipeline components with a directed graph in which components are the graph edges, their inputs and outputs are the graph nodes, and the paths through the graph are pipelines. To that end, we developed special data structures and a pipeline system algorithm. We demonstrate the applicability of our approach by implementing a format conversion pipeline for the fields of population genetics and genetic epidemiology, but our approach is also helpful in other fields where the use of multiple software is necessary to perform comprehensive analyses, such as gene expression and proteomics analyses. The project code, documentation and the Java executables are available under an open source license at "url"http://code.google.com/p/dynamic-pipeline"/url". The system has been tested on Linux and Windows platforms."/p" "p"Conclusions"/p" "p"Our graph-based approach enables the automatic creation of pipelines by compiling a specialised set of tools on demand, depending on the functionality required. It also allows the implementation of extensible and low-maintenance pipelines and contributes towards consolidating openness and collaboration in bioinformatics systems. It is targeted at pipeline developers and is suited for implementing applications with sequential execution steps and combined functionalities. In the format conversion application, the automatic combination of conversion tools increased both the number of possible conversions available to the user and the extensibility of the system to allow for future updates with new file formats. Document type: Article

Abstract

In this paper, we combine data from Uber Movement and from a representative household travel survey to constructs a weighted travel time index for the Metropolitan Region of São Paulo. The index is calculated based on the average travel time of Uber trips taken between each pair of traffic zone and in each hour between January 1st, 2016 to December 31, 2018. The index is weighted based on trips reported in a household travel survey that was designed to be statistically representative of all trips made in the city during a typical business day. We show that the index has a strong correlation with traditional measures of congestion, however, with a broader coverage of the road network. Finally, we use the index to run a multivariate ex-post analysis that estimates the effect of different events on traffic congestion in the city, including holidays, public transit strikes, road shutdowns, rain and major sport events. Document type: Article

Abstract

Background Recent advancements in high-throughput sequencing technologies have generated an unprecedented amount of genomic data that must be stored, processed, and transmitted over the network for sharing. Lossy genomic data compression, especially of the base quality values of sequencing data, is emerging as an efficient way to handle this challenge due to its superior compression performance compared to lossless compression methods. Many lossy compression algorithms have been developed for and evaluated using DNA sequencing data. However, whether these algorithms can be used on RNA sequencing (RNA-seq) data remains unclear. Results In this study, we evaluated the impacts of lossy quality value compression on common RNA-seq data analysis pipelines including expression quantification, transcriptome assembly, and short variants detection using RNA-seq data from different species and sequencing platforms. Our study shows that lossy quality value compression could effectively improve RNA-seq data compression. In some cases, lossy algorithms achieved up to 1.2-3 times further reduction on the overall RNA-seq data size compared to existing lossless algorithms. However, lossy quality value compression could affect the results of some RNA-seq data processing pipelines, and hence its impacts to RNA-seq studies cannot be ignored in some cases. Pipelines using HISAT2 for alignment were most significantly affected by lossy quality value compression, while the effects of lossy compression on pipelines that do not depend on quality values, e.g., STAR-based expression quantification and transcriptome assembly pipelines, were not observed. Moreover, regardless of using either STAR or HISAT2 as the aligner, variant detection results were affected by lossy quality value compression, albeit to a lesser extent when STAR-based pipeline was used. Our results also show that the impacts of lossy quality value compression depend on the compression algorithms being used and the compression levels if the algorithm supports setting of multiple compression levels. Conclusions Lossy quality value compression can be incorporated into existing RNA-seq analysis pipelines to alleviate the data storage and transmission burdens. However, care should be taken on the selection of compression tools and levels based on the requirements of the downstream analysis pipelines to avoid introducing undesirable adverse effects on the analysis results. Document type: Article

Abstract

Structure from Motion (SfM) is a pipeline that allows three-dimensional reconstruction starting from a collection of images. A typical SfM pipeline comprises different processing steps each of which tackles a different problem in the reconstruction pipeline. Each step can exploit different algorithms to solve the problem at hand and thus many different SfM pipelines can be built. How to choose the SfM pipeline best suited for a given task is an important question. In this paper we report a comparison of different state-of-the-art SfM pipelines in terms of their ability to reconstruct different scenes. We also propose an evaluation procedure that stresses the SfM pipelines using real dataset acquired with high-end devices as well as realistic synthetic dataset. To this end, we created a plug-in module for the Blender software to support the creation of synthetic datasets and the evaluation of the SfM pipeline. The use of synthetic data allows us to easily have arbitrarily large and diverse datasets with, in theory, infinitely precise ground truth. Our evaluation procedure considers both the reconstruction errors as well as the estimation errors of the camera poses used in the reconstruction. Document type: Article

Abstract

The data presented in this article relate to the research article "A quasi-3D approach for the assessment of induced AC interference on buried metallic pipelines" (Popoli et al., 2018) [1]. The current induced on a pipeline versus the distance between the overhead power line and the pipeline is presented. Various configurations of the overhead power line are considered. The calculations are based on method that combines 2D FEM simulations with circuital analysis. (C) 2019 Published by Elsevier Inc.

Abstract

The electromagnetic interference caused by overhead power lines on nonparallel underground pipelines is assessed in “A numerical model for the calculation of electromagnetic interference from power lines on nonparallel underground pipelines” (Popoli et al., 2020 [1]) by segmenting the pipeline path in a number of traits parallel to the power line. The analysis requires a multi-port electrical component to be extracted for each pipeline segment by means of finite element 2D analysis; circuit analysis can then be applied to the network composed of the cascade of the multi-port electrical components in order to calculate the induced voltages and currents on the pipeline. The data in this paper consist of matrices which represent the multi-port electrical components corresponding to the segments in which the pipeline has been subdivided. These matrices can then be used as constitutive relations in network analysis, as detailed in (Popoli et al., 2019 [2]), in order to find the induced pipeline voltages and currents for different intersection angles between the pipeline and overhead power line routings.

Abstract

Traffic congestion at bus bays has decreased the service efficiency of public transit seriously in China, so it is crucial to systematically study its theory and methods. However, the existing studies lack theoretical model on computing efficiency. Therefore, the calculation models of bus delay at bays are studied. Firstly, the process that buses are delayed at bays is analyzed, and it was found that the delay can be divided into entering delay and exiting delay. Secondly, the queueing models of bus bays are formed, and the equilibrium distribution functions are proposed by applying the embedded Markov chain to the traditional model of queuing theory in the steady state; then the calculation models of entering delay are derived at bays. Thirdly, the exiting delay is studied by using the queueing theory and the gap acceptance theory. Finally, the proposed models are validated using field-measured data, and then the influencing factors are discussed. With these models the delay is easily assessed knowing the characteristics of the dwell time distribution and traffic volume at the curb lane in different locations and different periods. It can provide basis for the efficiency evaluation of bus bays. Document type: Article

Abstract

Design concepts and algorithms were developed to address the eye tracking analysis issues that arise when (1) participants interrogate dynamic multielement objects that can overlap on the display and (2) visual angle error of the eye trackers is incapable of providing exact eye fixation coordinates. These issues were addressed by (1) developing dynamic areas of interests (AOIs) in the form of either convex or rectangular shapes to represent the moving and shape-changing multielement objects, (2) introducing the concept of AOI gap tolerance (AGT) that controls the size of the AOIs to address the overlapping and visual angle error issues, and (3) finding a near optimal AGT value. The approach was tested in the context of air traffic control (ATC) operations where air traffic controller specialists (ATCSs) interrogated multiple moving aircraft on a radar display to detect and control the aircraft for the purpose of maintaining safe and expeditious air transportation. In addition, we show how eye tracking analysis results can differ based on how we define dynamic AOIs to determine eye fixations on moving objects. The results serve as a framework to more accurately analyze eye tracking data and to better support the analysis of human performance. Document type: Article