Practical Pipeline Research Articles

MAC: identifying and correcting annotation for multi-nucleotide variations.

BackgroundNext-Generation Sequencing (NGS) technologies have rapidly advanced our understanding of human variation in cancer. To accurately translate the raw sequencing data into practical knowledge, annotation tools, algorithms and pipelines must be developed that keep pace with the rapidly evolving technology. Currently, a challenge exists in accurately annotating multi-nucleotide variants (MNVs). These tandem substitutions, when affecting multiple nucleotides within a single protein codon of a gene, result in a translated amino acid involving all nucleotides in that codon. Most existing variant callers report a MNV as individual single-nucleotide variants (SNVs), often resulting in multiple triplet codon sequences and incorrect amino acid predictions. To correct potentially misannotated MNVs among reported SNVs, a primary challenge resides in haplotype phasing which is to determine whether the neighboring SNVs are co-located on the same chromosome.ResultsHere we describe MAC (Multi-Nucleotide Variant Annotation Corrector), an integrative pipeline developed to correct potentially mis-annotated MNVs. MAC was designed as an application that only requires a SNV file and the matching BAM file as data inputs. Using an example data set containing 3024 SNVs and the corresponding whole-genome sequencing BAM files, we show that MAC identified eight potentially mis-annotated SNVs, and accurately updated the amino acid predictions for seven of the variant calls.ConclusionsMAC can identify and correct amino acid predictions that result from MNVs affecting multiple nucleotides within a single protein codon, which cannot be handled by most existing SNV-based variant pipelines. The MAC software is freely available and represents a useful tool for the accurate translation of genomic sequence to protein function.

A data-driven approximate causal inference model using the evidential reasoning rule

This paper aims to develop a data-driven approximate causal inference model using the newly-proposed evidential reasoning (ER) rule. The ER rule constitutes a generic conjunctive probabilistic reasoning process and generalises Dempster’s rule and Bayesian inference. The belief rule based (BRB) methodology was developed to model complicated nonlinear causal relationships between antecedent attributes and consequents on the basis of the ER algorithm and traditional IF-THEN rule-based systems, and in essence it keeps methodological consistency with Bayesian Network (BN). In this paper, we firstly introduce the ER rule and then analyse its inference patterns with respect to the bounded sum of individual support and the orthogonal sum of collective support from multiple pieces of independent evidence. Furthermore, we propose an approximate causal inference model with the kernel mechanism of data-based approximate causal modelling and optimal learning. The exploratory approximate causal inference model inherits the main strengths of BN, BRB and relevant techniques, and can potentially extend the boundaries of applying approximate causal inference to complex decision and risk analysis, system identification, fault diagnosis, etc. A numerical study on the practical pipeline leak detection problem demonstrates the applicability and capability of the proposed data-driven approximate causal inference model.

Pressure drop in loop pipe flow of fresh cemented coal gangue–fly ash slurry: Experiment and simulation

Cemented coal gangue–fly ash (CGF) mixtures are made by mixing cement, coal gangue, fly ash and water, and the CGFs are commonly used as the backfill materials for filling underground voids in coal mines. Generally, pipeline slurry transportation system is constructed to deliver the CGF into the underground, and pressure drop is one of the most significant technical indicators needs to be considered in designing the pipeline slurry transportation system. Therefore, a test loop system is employed to investigate the pressure drops of CGF slurries with different mix proportions. Based on the experimentally determined flow properties of the CGF slurry, a pipe flow model for predicting the flow behavior of the CGF slurry in the pipe loop is developed. This model is put into COMSOL Multiphysics to carry out simulation work, and then the simulation outcomes are compared with loop testing results. The favorable agreement between the model simulation and the loop test indicates that the developed model is valid and can be available to conduct further simulation exercise. By means of numerical simulation, effects of slurry volumetric flow rate and pumping pressure, as well as the combined effect of pipe inner diameter and flow velocity on pressure drop in the pipe loop flow of fresh CGF slurry are demonstrated. The obtained results in this study are helpful to the design of a practical CGF slurry pipeline transportation system, as well as to the selection of an appropriate pump capability.

Energy Equation Derivation of the Oil-Gas Flow in Pipelines

In the simulation of oil-gas pipeline multiphase flow, thermodynamic computation is an important process interacting with the hydraulic calculation and it influences the convergence of the program and the accuracy of the results. The form of the energy equation is the key to the thermodynamic computation. Based on the energy equation of oil-gas flow in pipeline, the Explicit Temperature Drop Formula (ETDF) is derived for oilgas steady state temperature calculation. This new energy equation has considered many factors, such as Joule-Thomson effect, pressure work, friction work and impact of terrain undulation and heat transfer Oil & Gas Science and Technology – Rev. IFP Energies nouvelles with the surroundings along the line. So it is an overall form of energy equation, which could describe the actual fact of multiphase pipeline accurately. Therefore, some standpoints in literatures on the temperature calculation of oil-gas two-phase flow in pipelines are reviewed. Elimination of temperature iteration loop and integration of the explicit temperature equation, instead of enthalpy energy equation, into the conjugated hydraulic and thermal computation have been found to improve the efficiency of algorithm. The calculation applied to both the component model, also applied to the black-oil model. This model is incorporated into the component model and black-oil model, respectively, and two simulations are carried out with two practical pipeline Yingmai-Yaha and Lufeng multiphase pipeline and the temperature results are compared with the simulation calculated by the OLGA and the measured. It is shown that this model has simulated the temperature distribution very well. Finally, we analyzed the influence of the specific heat capacity of oil and gas on the temperature of the mixture of fluids and the influence of the Joule-Thomson effect on the temperature distribution on the pipeline. It is shown that the Joule-Thomson coefficient is a key factor to well describe the oil-gas two-phase flow.

Infrared laser radar for practical airborne natural gas pipeline inspection

The problem of natural gas pipeline leak becomes increasingly serious.A practical airborne natural gas pipeline inspection laser radar which is based on tunable diode laser spectroscopy was developed.The operating principle of this instrument was introduced,the system configuration and method of design were discussed.The key technologies including high-accuracy laser frequency stabilization and real time calibration were further discussed.The analysis results of ground and airborne test proved that the instrument can be applied in practical project.

The Multi-Sized Slurry Flows in Horizontal Pipes : Innovated Models and Verification

Although multi-sized particles slurries are transported in practical pipelines, most reported correlations were proposed for single-size slurries. If the average diameter of solids is used to estimate the drag coefficient of multi-sized particles slurries, the hydraulic gradients with these correlations lead to considerable scatter of data . Kazanskij , Moro , and STSJ (Slurry Transport Society of Japan) [4] summarised some empirical equations of hydraulic gradient of slurry flow with experimental data. The Wasp method [5] recommended by Liu [6] has been used by designers of pipeline systems for predicting hydraulic gradient of compound slurries of homogeneous and heterogeneous flows. However, the method is limited for application to a wide range of transport conditions. Kaushal et al. [7] also discussed the limitations and attempted to modify the method. They concluded that the Wasp method provided reasonable accurate results at limited low concentrations. The purpose of this paper is to discuss the limitations of application of other researchers' correlations and to develop innovated models, based on the single-size slurry model of Seitshiro et al. [8] The analytical models depend on particle size distribution: (1) coarse-coarse model; for a slurry consisting of two fine particles in high concentration. The fine solids are defined as particles with sizes smaller than the critical diameter [9] in this study. For both models, it is assumed that the coarse solids in the slurry do not hinder each other's movements. Experiments were performed in a 1-inch transparent pipe with sand-bakelite mixed slurries. The data of Shook et al. , Boothroyde et al. , and that of this study were used to verify the application of the models. The analytical results suggest that the innovated models can be effective for designing slurry pipelines.

Fracture capacity of girth welded pipelines with 3D surface cracks subjected to biaxial loading conditions

Offshore pipelines installed by reeling method are subjected to large plastic strains. When the steel pipes are joined by girth welding, both surface and embedded cracks are inevitably initiated in welding zone. The pipe lines should have adequate resistance against both crack extension by tearing and unstable fracture during installation as well as during operation. However, common flaw assessment procedures, e.g. BS 7910:2005 [1], are not explicitly developed for such situations with large plastic strains. The main objective of the current paper is to find a way to assess fracture capability of a practical pipeline subject to large plastic deformation. In our study, the evolution of crack tip opening displacement (CTOD) of the pipeline with semi-eliptical surface crack in weld girth is investigated under biaxial loading conditions (uniaxial tensile and internal pressure) using three dimensional elastic–plastic finite element analysis. The effects of crack depth, ratio of semi-major axis to semi-minor axis and internal pressure are examined. The results show that at moderate levels of global strain, the variation of CTOD with global strain can be well approximated by a simple linear relationship under tensile loading as well as biaxial loading conditions. Comparing the fracture assessment for the welded pipe made by BS 7910:2005 with that made by our current study, it is found that the assessment from BS7910:2005 is over conservative. A CTOD-estimation method for strain -based fracture is suggested for the pipelines when the global strain is 3%.

A practical guide for the computational selection of residues to be experimentally characterized in protein families

In recent years, numerous biocomputational tools have been designed to extract functional and evolutionary information from multiple sequence alignments (MSAs) of proteins and genes. Most biologists working actively on the characterization of proteins from a single or family perspective use the MSA analysis to retrieve valuable information about amino acid conservation and the functional role of residues in query protein(s). In MSAs, adjustment of alignment parameters is a key point to improve the quality of MSA output. However, this issue is frequently underestimated and/or misunderstood by scientists and there is no in-depth knowledge available in this field. This brief review focuses on biocomputational approaches complementary to MSA to help distinguish functional residues in protein families. These additional analyses involve issues ranging from phylogenetic to statistical, which address the detection of amino acids pivotal for protein function at any level. In recent years, a large number of tools has been designed for this very purpose. Using some of these relevant, useful tools, we have designed a practical pipeline to perform in silico studies with a view to improving the characterization of family proteins and their functional residues. This review-guide aims to present biologists a set of specially designed tools to study proteins. These tools are user-friendly as they use web servers or easy-to-handle applications. Such criteria are essential for this review as most of the biologists (experimentalists) working in this field are unfamiliar with these biocomputational analysis approaches.

Inference analysis and adaptive training for belief rule based systems

Belief rule base (BRB) systems are an extension of traditional IF-THEN rule based systems and capable of capturing complicated nonlinear causal relationships between antecedent attributes and consequents. In a BRB system, various types of information with uncertainties can be represented using belief structures, and a belief rule is designed with belief degrees embedded in its possible consequents. For a set of inputs to antecedent attributes, inference in BRB is implemented using the evidential reasoning (ER) approach. In this paper, the inference mechanism of the ER algorithm is analyzed first and its patterns of monotonic inference and nonlinear approximation are revealed. For a practical BRB system, it is difficult to determine its parameters accurately by using only experts’ subjective knowledge. Moreover, the appropriate adjustment of the parameters of a BRB system using available historical data can lead to significant improvement on its prediction performance. In this paper, a training data selection scheme and an adaptive training method are developed for updating BRB parameters. Finally, numerical studies on a multi-modal function and a practical pipeline leak detection problem are conducted to illustrate the functionality of BRB systems and validate the performance of the adaptive training technique.

VDVR: Verifiable Volume Visualization of Projection-Based Data

Practical volume visualization pipelines are never without compromises and errors. A delicate and often-studied component is the interpolation of off-grid samples, where aliasing can lead to misleading artifacts and blurring, potentially hiding fine details of critical importance. The verifiable visualization framework we describe aims to account for these errors directly in the volume generation stage, and we specifically target volumetric data obtained via computed tomography (CT) reconstruction. In this case the raw data are the X-ray projections obtained from the scanner and the volume data generation process is the CT algorithm. Our framework informs the CT reconstruction process of the specific filter intended for interpolation in the subsequent visualization process, and this in turn ensures an accurate interpolation there at a set tolerance. Here, we focus on fast trilinear interpolation in conjunction with an octree-type mixed resolution volume representation without T-junctions. Efficient rendering is achieved by a space-efficient and locality-optimized representation, which can straightforwardly exploit fast fixed-function pipelines on GPUs.

Development of Third-Party Damage Monitoring System for Natural Gas Pipeline

In this paper, we develop a real time monitoring system to detect third-party damage on natural gas pipeline. When the damage due to third-party incidents causes an immediate rupture, the developed on-line monitoring system can help reducing the sequences of event at once. Moreover, since many third-party incidents cause damage that does not lead to immediate rupture but can grow with time, the developed on-line monitoring system can execute a significant role in reducing many third-party damage incidents. Also, when the damage is given at a point on natural gas pipeline, the acoustic wave is propagated very fast about 421.3 m/s. Therefore, the data processing time should be very short in order to detect precisely the impact position. Generally, the pipeline is laid under ground or sea and the length is very long. So a wireless data communication method is recommendable and the sensing positions are limited by laid circumstance and setting cost of sensors. The calculation and monitoring software is developed by an algorithm using the propagation speed of acoustic wave and data base system based on wireless communication and DSP systems. The developed monitoring system is examined by field testing at Balan pilot plant, KOGAS being done in order to demonstrate its validity through reactive detection of third-party contact with pipelines. Furthermore, the development system was set at the practical pipelines such as an offshore pipeline between two islands Yul-Do and Youngjong-Do, and a land branch of Pyoungtaek, Korea and it has been operating in real time.

A damage model for assessing pipeline safety in corrosion environments

Considering such practical pipeline service conditions in the petroleum transportation field as corrosion from harmful media (H2S, CO2 etc.) and load from the pressure of flowing petroleum as key factors, the degradation of the mechanical properties of pipeline steels and the corresponding variations in stress states are studied. A damage variable is introduced to reflect the degradation in the mechanical properties of the pipeline due to corrosion. A diluted solution approach is proposed to model the corrosion process of harmful media within the pipeline and the distribution of the damage variable along the radial direction of the pipeline is derived. An approach to the safety evaluation of damaged pipeline is proposed by comparing the instant properties of pipeline steels with servicing conditions.

沈降性スラリーの水平管路内流れにおける速度分布の近似解法

It is to be noted that velocity profile is an important parameter in regarding frictional phenomena between solid particles and pipe wall, critical deposit velocity, and sorting mechanism near the bed in settling slurry flows in a horizontal pipe. We propose in this paper two analytical models which could be used for the calculation of the velocity profiles in practical pipeline design: an acceleration model and a nearly steady flow model. Based on the hypothesis that steady slurry flow would be produced through the encounter of water flow to no moving suspended solid particles with a fixed distribution of concentration in water, the models have been derived by the analysis of the change in momentums both of solid particles and water with time, and by the analysis of equilibrium conditions of forces acting a particle in a nearly steady flow. Predictions from the models are compared with experimental results obtained from published papers, and are verified to be reliable.

粒体の空気輸送特性におよぼす気流速度の影響

The flow characteristics of pneumatic conveying containing unstable flow regions were studied by making use of nearly practical scale pipelines in abroad air velocity range of approximately 1-20m/s.The variations in the pressure in the tank and pipe, and the conveying flow pattern and conveying efficiency are intimately related to each other. A conveying state is classified into three regions: the suspension, plug conveying regions and the unstable one between those regions. In the unstable region, the flow pattern of plug conveying and suspension after blowing off the plugs are mutually generated.

Comments on important genetic topics from papers in other journals: Disease and evolution

<h3>Abstract</h3> The process of designing biomolecules, in particular proteins, is witnessing a rapid change in available tooling and approaches, moving from design through physicochemical force fields, to producing plausible, complex sequences fast via end-to-end differentiable statistical models. To achieve conditional and controllable protein design, researchers at the interface of artificial intelligence and biology leverage advances in natural language processing (NLP) and computer vision techniques, coupled with advances in computing hardware to learn patterns from growing biological databases, curated annotations thereof, or both. Once learned, these patterns can be leveraged to provide novel insights into mechanistic biology and the design of biomolecules. However, navigating and understanding the practical applications for the many recent protein design tools is complex. To facilitate this, we 1) document recent advances in deep learning (DL) assisted protein design from the last three years, 2) present a practical pipeline that allows to go from <i>de novo</i>-generated sequences to their predicted properties and web-powered visualization within minutes, and 3) leverage it to suggest a generated protein sequence which might be used to engineer a biosynthetic gene cluster to produce a molecular glue-like compound. Lastly, we discuss challenges and highlight opportunities for the protein design field. <h3>Availability</h3> pLM generated and UniRef50 sampled sequence sets and predictions are available at http://data.bioembeddings.com/public/design. Code-base and Notebooks for analysis are available at https://github.com/hefeda/PGP. An online version of <b>Table 1</b> can be found at https://github.com/hefeda/design_tools.

Electrostatic flowsensor

The effect of flow and tube materials on the magnitude of electrostatic charge induced by streaming electrification in oil hydraulic pipelines has been experimentally investigated. A simple model based on a separation and a relaxation of charge can explain quantitatively the static electricity distribution in practical hydraulic pipelines. The results indicate that negative charge appears on an insulated tube wall and the magnitude of the electrostatic charge per unit inner area of the tube wall is a linear function of flow rate. A new type of flowsensor was developed using the proportionality of the electrostatic charge to the flow rate and called an ‘Electrostatic Flowsensor’.

Analysis of Capsule Pipeline System by the Method of Characteristics : Numerical Analysis and Comparison with Transport Experiment

Based on the calculation of our previous paper, the transport characteristics of capsule in pipelines are examined by varying the pipe inlet pressure, pipe length and pipe diameter, and further it is shown that by the use of an exhaust valve placed at the middle of the pipeline an efficient transport of capsule can be achieved. To confirm the numerical analysis some experimental works are carried out and it is found that the numerical analysis is valid. The measurements according to Cudlin and Harman and those obtained with practical capsule pipelines are qualitatively predicted by the present calculation as well.

Patterns of canine gastric electrical activity.

Patterns of canine gastric electrical activity.