670 resultados para pipeline


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Since El Salvador’s civil war formally ended in 1992 the small Central American nation has undergone profound social changes and significant reforms. However, few changes have been as important or as devastating as the nation’s emergence as a central hub in the transnational criminal “pipeline” or series of recombinant, overlapping chains of routes and actors that illicit organizations use to traffic in drugs, money weapons, human being, endangered animals and other products. The erasing of the once-clear ideological lines that drove the civil war and the ability of erstwhile enemies to join forces in criminal enterprises in the post-war period is an enduring and dangerous characteristic of El Salvador’s transnational criminal evolution. Trained, elite cadres from both sides, with few legitimate job opportunities, found their skills were marketable in the growing criminal structures. The groups moved from kidnapping and extortion to providing protection services to transnational criminal organizations to becoming integral parts of the organizations themselves. The demand for specialized military and transportation services in El Salvador have exploded as the Mexican DTOs consolidate their hold on the cocaine market and their relationships with the transportista networks, which is still in flux. The value of their services has risen dramatically also because of the fact that multiple Mexican DTOs, at war with each other in Mexico and seeking to physically control the geographic space of the lucrative pipeline routes in from Guatemala to Panama, are eager to increase their military capabilities and intelligence gathering capacities. The emergence of multiple non-state armed groups, often with significant ties to the formal political structure (state) through webs of judicial, legislative and administrative corruption, has some striking parallels to Colombia in the 1980s, where multiple types of violence ultimately challenged the sovereignty of state and left a lasting legacy of embedded corruption within the nation’s political structure. Organized crime in El Salvador is now transnational in nature and more integrated into stronger, more versatile global networks such as the Mexican DTOs. It is a hybrid of both local crime – with gangs vying for control off specific geographic space so they can extract payment for the safe passage of illicit products – and transnational groups that need to use that space to successfully move their products. These symbiotic relationships are both complex and generally transient in nature but growing more consolidated and dangerous.

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Trenchless methods have been considered to be a viable solution for pipeline projects in urban areas. Their applicability in pipeline projects is expected to increase with the rapid advancements in technology and emerging concerns regarding social costs related to trenching methods. Selecting appropriate project delivery system (PDS) is a key to the success of trenchless projects. To ensure success of the project, the selected project delivery should be tailored to trenchless project specific characteristics and owner needs, since the effectiveness of project delivery systems differs based on different project characteristics and owners requirements. Since different trenchless methods have specific characteristics such rate of installation, lengths of installation, and accuracy, the same project delivery systems may not be equally effective for different methods. The intent of this paper is to evaluate the appropriateness of different PDS for different trenchless methods. PDS are examined through a structured decision-making process called Fuzzy Delivery System Selection Model (FDSSM). The process of incorporating the impacts of: (a) the characteristics of trenchless projects and (b) owners’ needs in the FDSSM is performed by collecting data using questionnaires deployed to professionals involved in the trenchless industry in order to determine the importance of delivery systems selection attributes for different trenchless methods, and then analyzing this data. The sensitivity of PDS rankings with respect to trenchless methods is considered in order to evaluate whether similar project delivery systems are equally effective in different trenchless methods. The effectiveness of PDS with respect to attributes is defined as follows: a project delivery system is most effective with respect to an attribute (e.g., ability to control growth in costs ) if there is no project delivery system that is more effective than that PDS. The results of this study may assist trenchless project owners to select the appropriate PDS for the trenchless method selected.

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Background: During alternative splicing, the inclusion of an exon in the final mRNA molecule is determined by nuclear proteins that bind cis-regulatory sequences in a target pre-mRNA molecule. A recent study suggested that the regulatory codes of individual RNA-binding proteins may be nearly immutable between very diverse species such as mammals and insects. The model system Drosophila melanogaster therefore presents an excellent opportunity for the study of alternative splicing due to the availability of quality EST annotations in FlyBase. Methods: In this paper, we describe an in silico analysis pipeline to extract putative exonic splicing regulatory sequences from a multiple alignment of 15 species of insects. Our method, ESTs-to-ESRs (E2E), uses graph analysis of EST splicing graphs to identify mutually exclusive (ME) exons and combines phylogenetic measures, a sliding window approach along the multiple alignment and the Welch’s t statistic to extract conserved ESR motifs. Results: The most frequent 100% conserved word of length 5 bp in different insect exons was “ATGGA”. We identified 799 statistically significant “spike” hexamers, 218 motifs with either a left or right FDR corrected spike magnitude p-value < 0.05 and 83 with both left and right uncorrected p < 0.01. 11 genes were identified with highly significant motifs in one ME exon but not in the other, suggesting regulation of ME exon splicing through these highly conserved hexamers. The majority of these genes have been shown to have regulated spatiotemporal expression. 10 elements were found to match three mammalian splicing regulator databases. A putative ESR motif, GATGCAG, was identified in the ME-13b but not in the ME-13a of Drosophila N-Cadherin, a gene that has been shown to have a distinct spatiotemporal expression pattern of spliced isoforms in a recent study. Conclusions: Analysis of phylogenetic relationships and variability of sequence conservation as implemented in the E2E spikes method may lead to improved identification of ESRs. We found that approximately half of the putative ESRs in common between insects and mammals have a high statistical support (p < 0.01). Several Drosophila genes with spatiotemporal expression patterns were identified to contain putative ESRs located in one exon of the ME exon pairs but not in the other.

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Bio-systems are inherently complex information processing systems. Furthermore, physiological complexities of biological systems limit the formation of a hypothesis in terms of behavior and the ability to test hypothesis. More importantly the identification and classification of mutation in patients are centric topics in today's cancer research. Next generation sequencing (NGS) technologies can provide genome-wide coverage at a single nucleotide resolution and at reasonable speed and cost. The unprecedented molecular characterization provided by NGS offers the potential for an individualized approach to treatment. These advances in cancer genomics have enabled scientists to interrogate cancer-specific genomic variants and compare them with the normal variants in the same patient. Analysis of this data provides a catalog of somatic variants, present in tumor genome but not in the normal tissue DNA. In this dissertation, we present a new computational framework to the problem of predicting the number of mutations on a chromosome for a certain patient, which is a fundamental problem in clinical and research fields. We begin this dissertation with the development of a framework system that is capable of utilizing published data from a longitudinal study of patients with acute myeloid leukemia (AML), who's DNA from both normal as well as malignant tissues was subjected to NGS analysis at various points in time. By processing the sequencing data at the time of cancer diagnosis using the components of our framework, we tested it by predicting the genomic regions to be mutated at the time of relapse and, later, by comparing our results with the actual regions that showed mutations (discovered at relapse time). We demonstrate that this coupling of the algorithm pipeline can drastically improve the predictive abilities of searching a reliable molecular signature. Arguably, the most important result of our research is its superior performance to other methods like Radial Basis Function Network, Sequential Minimal Optimization, and Gaussian Process. In the final part of this dissertation, we present a detailed significance, stability and statistical analysis of our model. A performance comparison of the results are presented. This work clearly lays a good foundation for future research for other types of cancer.^

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Pseudomonas aeruginosa, a Gram-negative bacterium, an opportunistic pathogen that infects individuals suffering from reduced immunity or damaged tissue. The treatment of these infections has become a major problem due to its increasing antibiotic resistance. Many multi-drug resistant isolates of P. aeruginosa can thwart most antibiotic classes including ?- lactams, fluoroquinolones, and aminoglycosides. Its ability to combat ?-lactams is in part due to expression of AmpC, a major chromosomally encoded ?-lactamase. The expression of ampC is positively regulated by AmpR. Besides antibiotic resistance, AmpR is an important regulator of various factors that are required for establishing acute and chronic infections. Loss of ampR makes P. aeruginosa susceptible to ?-lactams and less virulent than the wild type. We hypothesize that AmpR is a potential therapeutic target. In the absence of new drugs in the pipeline, the aim of this study is to find an AmpR-specific inhibitor to assist and improve the use of currently available ?- lactam treatment. A small-molecule library from Torrey Pines Institute will be used in this study. Two reporter systems, lux and lacZ, fused to a PampC promotor will be used to assess AmpR activity. Positive hits will be those that inhibit 50% PampC activity in the presence of sub inhibitory concentration of imipenem, a ?- lactam. The top positive hits will be screened for their ability to cause human cell-cytotoxicity. The non-cytotoxic hits will be assessed for their ability to affect P. aeruginosa virulence and antibiotic resistance using various in vitro assays. Determination of potential AmpR inhibitors will prove to be useful in fighting off infections and may save countless patients suffering from these infections.

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Computational Intelligence Methods have been expanding to industrial applications motivated by their ability to solve problems in engineering. Therefore, the embedded systems follow the same idea of using computational intelligence tools embedded on machines. There are several works in the area of embedded systems and intelligent systems. However, there are a few papers that have joined both areas. The aim of this study was to implement an adaptive fuzzy neural hardware with online training embedded on Field Programmable Gate Array – FPGA. The system adaptation can occur during the execution of a given application, aiming online performance improvement. The proposed system architecture is modular, allowing different configurations of fuzzy neural network topologies with online training. The proposed system was applied to: mathematical function interpolation, pattern classification and selfcompensation of industrial sensors. The proposed system achieves satisfactory performance in both tasks. The experiments results shows the advantages and disadvantages of online training in hardware when performed in parallel and sequentially ways. The sequentially training method provides economy in FPGA area, however, increases the complexity of architecture actions. The parallel training method achieves high performance and reduced processing time, the pipeline technique is used to increase the proposed architecture performance. The study development was based on available tools for FPGA circuits.

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Problems associated to longitudinal interactions in buried pipelines are characterized as three-dimensional and can lead to different soil-pipe issues. Despite the progress achieved in research on buried pipelines, little attention has been given to the three-dimensional nature of the problem throughout the last decades. Most of researches simplify the problem by considering it in plane strain condition. This dissertation aims to present a study on the behavior of buried pipelines under local settlement or elevation, using three-dimensional simulations. Finite element code Plaxis 3D was used for the simulations. Particular aspects of the numerical modeling were evaluated and parametric analyzes were performed, was investigated the effects of soil arching in three-dimensional form. The main variables investigated were as follows: relative density, displacement of the elevation or settlement zone, elevated zone size, height of soil cover and pipe diameter/thickness ratio. The simulations were performed in two stages. The first stage was involved the validation of the numerical analysis using the physical models put forward by Costa (2005). In the second stage, numerical analyzes of a full-scale pipeline subjected to a localized elevation were performed. The obtained results allowed a detailed evaluation of the redistribution of stresses in the soil mass and the deflections along the pipe. It was observed the reduction of stresses in the soil mass and pipe deflections when the height of soil cover was decreased on regions of the pipe subjected to elevation. It was also shown for the analyzed situation that longitudinal thrusts were higher than vi circumferential trusts and exceeded the allowable stresses and deflections. Furthermore, the benefits of minimizing stress with technical as the false trench, compressible cradle and a combination of both applied to the simulated pipeline were verified

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The continuous evolution of integrated circuit technology has allowed integrating thousands of transistors on a single chip. This is due to the miniaturization process, which reduces the diameter of wires and transistors. One drawback of this process is that the circuit becomes more fragile and susceptible to break, making the circuit more susceptible to permanent faults during the manufacturing process as well as during their lifetime. Coarse Grained Reconfigurable Architectures (CGRAs) have been used as an alternative to traditional architectures in an attempt to tolerate such faults due to its intrinsic hardware redundancy and high performance. This work proposes a fault tolerance mechanism in a CGRA in order to increase the architecture fault tolerance even considering a high fault rate. The proposed mechanism was added to the scheduler, which is the mechanism responsible for mapping instructions onto the architecture. The instruction mapping occurs at runtime, translating binary code without the need for recompilation. Furthermore, to allow faster implementation, instruction mapping is performed using a greedy module scheduling algorithm, which consists of a software pipeline technique for loop acceleration. The results show that, even with the proposed mechanism, the time for mapping instructions is still in order of microseconds. This result allows that instruction mapping process remains at runtime. In addition, a study was also carried out mapping scheduler rate. The results demonstrate that even at fault rates over 50% in functional units and interconnection components, the scheduler was able to map instructions onto the architecture in most of the tested applications.

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An important problem faced by the oil industry is to distribute multiple oil products through pipelines. Distribution is done in a network composed of refineries (source nodes), storage parks (intermediate nodes), and terminals (demand nodes) interconnected by a set of pipelines transporting oil and derivatives between adjacent areas. Constraints related to storage limits, delivery time, sources availability, sending and receiving limits, among others, must be satisfied. Some researchers deal with this problem under a discrete viewpoint in which the flow in the network is seen as batches sending. Usually, there is no separation device between batches of different products and the losses due to interfaces may be significant. Minimizing delivery time is a typical objective adopted by engineers when scheduling products sending in pipeline networks. However, costs incurred due to losses in interfaces cannot be disregarded. The cost also depends on pumping expenses, which are mostly due to the electricity cost. Since industrial electricity tariff varies over the day, pumping at different time periods have different cost. This work presents an experimental investigation of computational methods designed to deal with the problem of distributing oil derivatives in networks considering three minimization objectives simultaneously: delivery time, losses due to interfaces and electricity cost. The problem is NP-hard and is addressed with hybrid evolutionary algorithms. Hybridizations are mainly focused on Transgenetic Algorithms and classical multi-objective evolutionary algorithm architectures such as MOEA/D, NSGA2 and SPEA2. Three architectures named MOTA/D, NSTA and SPETA are applied to the problem. An experimental study compares the algorithms on thirty test cases. To analyse the results obtained with the algorithms Pareto-compliant quality indicators are used and the significance of the results evaluated with non-parametric statistical tests.

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This thesis investigated the risk of accidental release of hydrocarbons during transportation and storage. Transportation of hydrocarbons from an offshore platform to processing units through subsea pipelines involves risk of release due to pipeline leakage resulting from corrosion, plastic deformation caused by seabed shakedown or damaged by contact with drifting iceberg. The environmental impacts of hydrocarbon dispersion can be severe. Overall safety and economic concerns of pipeline leakage at subsea environment are immense. A large leak can be detected by employing conventional technology such as, radar, intelligent pigging or chemical tracer but in a remote location like subsea or arctic, a small chronic leak may be undetected for a period of time. In case of storage, an accidental release of hydrocarbon from the storage tank could lead pool fire; further it could escalate to domino effects. This chain of accidents may lead to extremely severe consequences. Analyzing past accident scenarios it is observed that more than half of the industrial domino accidents involved fire as a primary event, and some other factors for instance, wind speed and direction, fuel type and engulfment of the compound. In this thesis, a computational fluid dynamics (CFD) approach is taken to model the subsea pipeline leak and the pool fire from a storage tank. A commercial software package ANSYS FLUENT Workbench 15 is used to model the subsea pipeline leakage. The CFD simulation results of four different types of fluids showed that the static pressure and pressure gradient along the axial length of the pipeline have a sharp signature variation near the leak orifice at steady state condition. Transient simulation is performed to obtain the acoustic signature of the pipe near leak orifice. The power spectral density (PSD) of acoustic signal is strong near the leak orifice and it dissipates as the distance and orientation from the leak orifice increase. The high-pressure fluid flow generates more noise than the low-pressure fluid flow. In order to model the pool fire from the storage tank, ANSYS CFX Workbench 14 is used. The CFD results show that the wind speed has significant contribution on the behavior of pool fire and its domino effects. The radiation contours are also obtained from CFD post processing, which can be applied for risk analysis. The outcome of this study will be helpful for better understanding of the domino effects of pool fire in complex geometrical settings of process industries. The attempt to reduce and prevent risks is discussed based on the results obtained from the numerical simulations of the numerical models.

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Due to relative ground movement, buried pipelines experience geotechnical loads. The imposed geotechnical loads may initiate pipeline deformations that affect system serviceability and integrity. Engineering guidelines (e.g., ALA, 2005; Honegger and Nyman, 2001) provide the technical framework to develop idealized structural models to analyze pipe‒soil interaction events and assess pipe mechanical response. The soil behavior is modeled using discrete springs that represent the geotechnical loads per unit pipe length developed during the interaction event. Soil forces are defined along three orthogonal directions (i.e., axial, lateral and vertical) to analyze the response of pipelines. Nonlinear load-displacement relationships of soil defined by a spring, is independent of neighboring spring elements. However, recent experimental and numerical studies demonstrate significant coupling effects during oblique (i.e., not along one of the orthogonal axes) pipe‒soil interaction events. In the present study, physical modeling using a geotechnical centrifuge was conducted to improve the current understanding of soil load coupling effects of buried pipes in loose and dense sand. A section of pipeline, at shallow burial depth, was translated through the soil at different oblique angles in the axial-lateral plane. The force exerted by the soil on pipe is critically examined to assess the significance of load coupling effects and establish a yield envelope. The displacements required to soil yield force are also examined to assess potential coupling in mobilization distance. A set of laboratory tests were conducted on the sand used for centrifuge modeling to find the stress-strain behavior of sand, which was used to examine the possible mechanisms of centrifuge model test. The yield envelope, deformation patterns, and interpreted failure mechanisms obtained from centrifuge modeling are compared with other physical modeling and numerical simulations available in the literature.

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In oil and gas pipeline operations, the gas, oil, and water phases simultaneously move through pipe systems. The mixture cools as it flows through subsea pipelines, and forms a hydrate formation region, where the hydrate crystals start to grow and may eventually block the pipeline. The potential of pipe blockage due to hydrate formation is one of the most significant flow-assurance problems in deep-water subsea operations. Due to the catastrophic safety and economic implications of hydrate blockage, it is important to accurately predict the simultaneous flow of gas, water, and hydrate particles in flowlines. Currently, there are few or no studies that account for the simultaneous effects of hydrate growth and heat transfer on flow characteristics within pipelines. This thesis presents new and more accurate predictive models of multiphase flows in undersea pipelines to describe the simultaneous flow of gas, water, and hydrate particles through a pipeline. A growth rate model for the hydrate phase is presented and then used in the development of a new three-phase model. The conservation equations of mass, momentum, and energy are formulated to describe the physical phenomena of momentum and heat transfer between the fluid and the wall. The governing equations are solved based on an analytical-numerical approach using a Newton-Raphson method for the nonlinear equations. An algorithm was developed in Matlab software to solve the equations from the inlet to the outlet of the pipeline. The developed models are validated against a single-phase model with mixture properties, and the results of comparative studies show close agreement. The new model predicts the volume fraction and velocity of each phase, as well as the mixture pressure and temperature profiles along the length of the pipeline. The results from the hydrate growth model reveal the growth rate and location where the initial hydrates start to form. Finally, to assess the impact of certain parameters on the flow characteristics, parametric studies have been conducted. The results show the effect of a variation in the pipe diameter, mass flow rate, inlet pressure, and inlet temperature on the flow characteristics and hydrate growth rates.

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Formation of hydrates is one of the major flow assurance problems faced by the oil and gas industry. Hydrates tend to form in natural gas pipelines with the presence of water and favorable temperature and pressure conditions, generally low temperatures and corresponding high pressures. Agglomeration of hydrates can result in blockage of flowlines and equipment, which can be time consuming to remove in subsea equipment and cause safety issues. Natural gas pipelines are more susceptible to burst and explosion owing to hydrate plugging. Therefore, a rigorous risk-assessment related to hydrate formation is required, which assists in preventing hydrate blockage and ensuring equipment integrity. This thesis presents a novel methodology to assess the probability of hydrate formation and presents a risk-based approach to determine the parameters of winterization schemes to avoid hydrate formation in natural gas pipelines operating in Arctic conditions. It also presents a lab-scale multiphase flow loop to study the effects of geometric and hydrodynamic parameters on hydrate formation and discusses the effects of geometric and hydrodynamic parameters on multiphase development length of a pipeline. Therefore, this study substantially contributes to the assessment of probability of hydrate formation and the decision making process of winterization strategies to prevent hydrate formation in Arctic conditions.

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Lo scopo della tesi è creare un’architettura in FPGA in grado di ricavare informazioni 3D da una coppia di sensori stereo. La pipeline è stata realizzata utilizzando il System-on-Chip Zynq, che permette una stretta interazione tra la parte hardware realizzata in FPGA e la CPU. Dopo uno studio preliminare degli strumenti hardware e software, è stata realizzata l’architettura base per la scrittura e la lettura di immagini nella memoria DDR dello Zynq. In seguito l’attenzione si è spostata sull’implementazione di algoritmi stereo (rettificazione e stereo matching) su FPGA e nella realizzazione di una pipeline in grado di ricavare accurate mappe di disparità in tempo reale acquisendo le immagini da una camera stereo.