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In this study, we propose a method based on phase space reconstruction to estimate the short-term future behavior of pressure signals in pipelines. The pressure time series data were obtained from an IoT experimental model conducted in the laboratory. The proposed hydraulic system demonstrated the presence of traces of weak chaos in the time series of the pressure signal. Fractal dimension analysis revealed a complex fractal structure in the data, indicating the existence of nonlinear dynamics. Similarly, Lyapunov coefficients, divergent trajectories, and autocorrelation analysis confirmed the presence of weak chaos in the time series. The results demonstrated the existence of apparently chaotic patterns that follow the theory proposed by Kolmogorov for deterministic dynamic systems that exhibit apparently random behaviors. Phase space reconstruction allowed us to show the dynamic characteristics of the signal so that short-term predictions were stable. Finally, the study of strange attractors in pipeline pressure time series can have significant contributions to anomaly detection.•A methodology is proposed for the reconstruction of the phase space to estimate the short-term future behavior of pressure signals in pipelines in real time.•The analysis of the proposed hydraulic system revealed some indications of weak chaos in the time series of the pressure signal obtained experimentally.•The methodology implemented and the results of this study showed that the short-term predictions were very accurate and consistent; Chaotic patterns were also identified that support the theory proposed by Kolmogorov.

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The past few years have seen significant advances in the study of complex microbial communities associated with the evolution of sequencing technologies and increasing adoption of whole genome shotgun sequencing methods over the once more traditional Amplicon-based methods. Although these advances have broadened the horizon of meta-omic analyses in planetary health, human health, and ecology from simple sample composition studies to comprehensive taxonomic and metabolic profiles, there are still significant challenges in processing these data. First, there is a widespread lack of standardization in data processing, including software choices and the ease of installing and running attendant software. This can lead to several inconsistencies, making comparing results across studies and reproducing original results difficult. We argue that these drawbacks are especially evident in metatranscriptomic analysis, with most analyses relying on ad hoc scripts instead of pipelines implemented in workflow managers. Additional challenges rely on integrating meta-omic data, since methods have to consider the biases in the library preparation and sequencing methods and the technical noise that can arise from it. Here, we critically discuss the current limitations in metagenomics and metatranscriptomics methods with a view to catalyze future innovations in the field of Planetary Health, ecology, and allied fields of life sciences. We highlight possible solutions for these constraints to bring about more standardization, with ease of installation, high performance, and reproducibility as guiding principles.

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The oil spill environmental sensitivity index is a key tool for preventing and dealing with environmental disasters caused by oil spills. This study aims to review the available literature on the subject and highlight the importance of methodological advances to improve how the index is applied in continental areas, especially in regions crossed by pipelines. Most current mapping techniques focus on coastal areas and fail to consider the stretches of land that are vulnerable to geodynamic natural disasters. In this context, the need to implement environmental sensitivity indices specific for pipelines has become urgent. This study also presents an overview of the main accidents around the world and a detailed analysis of the history of Brazilian disasters related to oil spills along continental stretches, with a focus on pipelines and natural disasters. In addition, this work highlights the importance of carrying out new research in mountainous areas of Brazil and is aimed at preventing Natechs (natural hazard triggering technological disasters) and improving contingency plans. As a result, several pathways have been identified, which involves the necessity of resolving gaps in terrestrial environmental sensitivity mapping methodologies, particularly as applied to pipelines. Furthermore, solutions must be capable of integrating terrestrial, fluvial, coastal, and maritime environmental sensitivity mapping techniques. Moreover, the need to implement dynamic risk monitoring systems in real time is critical to help manage such a complex problem.

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Background: Advancements in DNA sequencing technology have transformed the field of bacterial genomics, allowing for faster and more cost effective chromosome level assemblies compared to a decade ago. However, transforming raw reads into a complete genome model is a significant computational challenge due to the varying quality and quantity of data obtained from different sequencing instruments, as well as intrinsic characteristics of the genome and desired analyses. To address this issue, we have developed a set of container-based pipelines using Nextflow, offering both common workflows for inexperienced users and high levels of customization for experienced ones. Their processing strategies are adaptable based on the sequencing data type, and their modularity enables the incorporation of new components to address the community's evolving needs. Methods: These pipelines consist of three parts: quality control, de novo genome assembly, and bacterial genome annotation. In particular, the genome annotation pipeline provides a comprehensive overview of the genome, including standard gene prediction and functional inference, as well as predictions relevant to clinical applications such as virulence and resistance gene annotation, secondary metabolite detection, prophage and plasmid prediction, and more. Results: The annotation results are presented in reports, genome browsers, and a web-based application that enables users to explore and interact with the genome annotation results. Conclusions: Overall, our user-friendly pipelines offer a seamless integration of computational tools to facilitate routine bacterial genomics research. The effectiveness of these is illustrated by examining the sequencing data of a clinical sample of Klebsiella pneumoniae.

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The USA recently announced it is planning on deploying 30 GW of offshore wind by 2030 (national goal for offshore wind). Part of this development will be in the Gulf of Mexico, which has both wind potential and pre-existing oil and gas pipelines, only a portion of which is currently being used. Examining whether these assets can be used to economically transport power back from future Gulf wind farms should be a first step for developers. The question of whether laying new high-voltage direct current submarine cable versus repurposing pipeline to transport wind power will be examined. This paper looks at the hydrogen market and its use to transport wind power, what it would take to retrofit pipeline to carry hydrogen, a cost analysis given available data, and a look at potential policy support. There is a need to assess pipelines individually; however, retrofitting existing infrastructure should be considered an alternative to laying new submarine transmission cables. Additionally, alleviating the issue of oil and gas stranded assets through pipeline reuse may provide political support in hastening the energy transition.

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ABSTRACT Biomethane can readily replace fossil fuels including natural gas, which has similar physical and chemical properties. In Brazil, municipal solid waste is predominantly disposed of in landfills. Landfill gas is mostly employed for electricity generation, but still at low levels when compared to the existing potential. Production of biomethane from landfill gas may be an alternative to exploit the existing potential, but Brazil's pipeline network is rather limited and concentrated along the country's coast. In this context, the research sought to identify the locational viability of using landfill gas to produce biomethane and injecting it into pipelines, considering the available potential and its proximity to Brazil's existing pipeline network. The QGis software was used to integrate the information. Territorial arrangements with a biomethane production capacity of more than 15,000 Nm3 day−1 and located up to 50 km from the pipeline network were considered feasible. The research estimated a potential production equivalent to 3,407,027 Nm3 day−1 of biomethane from landfills in Brazil. This potential corresponds to 6% of country's natural gas consumption in 2019 and is almost 32 times greater than current production of biomethane from all substrates used with this purpose in that year. The results indicate the suitability of using geographic information systems to identify regions that can benefit from the production of biomethane from landfill gas using the existing natural gas pipelines as an alternative to the electricity generation and provides relevant subsidies to the formulation of more efficient public policies in both the sanitation and energy sectors.

RESUMO O biometano pode substituir facilmente os combustíveis fósseis, incluindo o gás natural, que possui propriedades físicas e químicas similares. No Brasil, os resíduos sólidos urbanos são descartados predominantemente em aterros sanitários. O gás dos aterros sanitários é empregado principalmente na geração de eletricidade, mas ainda em níveis baixos quando comparado ao potencial existente. A produção de biometano a partir do gás de aterro pode ser uma alternativa para explorar o potencial existente, mas a rede de gasodutos do Brasil é bastante limitada e concentrada ao longo da costa do país. Nesse contexto, esta pesquisa buscou identificar a viabilidade locacional do uso de gás de aterro sanitário para produzir biometano e injetá-lo em dutos, considerando o potencial disponível e sua proximidade com a rede de dutos existente no Brasil. O software QGis foi utilizado para integrar as informações. Foram considerados viáveis arranjos territoriais com uma capacidade de produção de biometano maior que 15.000 Nm3 dia−1 e localizados a até 50 km da rede de gasodutos. A pesquisa estimou uma produção potencial equivalente a 3.407.027 Nm3 dia−1 de biometano a partir de aterros sanitários no Brasil. Esse potencial corresponde a 6% do consumo de gás natural do país em 2019 e é quase 32 vezes maior que a produção de biometano de todos os substratos utilizados com essa finalidade naquele ano. Os resultados indicam a adequação do uso de sistemas de informação geográfica para identificar regiões que podem se beneficiar da produção de biometano a partir de gás de aterro sanitário, utilizando os gasodutos de gás natural existentes como alternativa à geração de eletricidade e fornece subsídios relevantes para a formulação de políticas públicas mais eficientes, tanto no setor de saneamento quanto no de energia.

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This paper addresses the two simultaneous leak diagnosis problem in pipelines based on a state vector reconstruction as a strategy to improve water shortages in large cities by only considering the availability of the flow rate and pressure head measurements at both ends of the pipeline. The proposed algorithm considers the parameters of both leaks as new state variables with constant dynamics, which results in an extended state representation. By applying a suitable persistent input, an invertible mapping in x can be obtained as a function of the input and output, including their time derivatives of the third-order. The state vector can then be reconstructed by means of an algebraic-like observer through the computation of time derivatives using a Numerical Differentiation with Annihilatorsconsidering its inherent noise rejection properties. Experimental results showed that leak parameters were reconstructed with accuracy using a test bed plant built at Cinvestav Guadalajara.

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BACKGROUND: Biomolecular interactions that modulate biological processes occur mainly in cavities throughout the surface of biomolecular structures. In the data science era, structural biology has benefited from the increasing availability of biostructural data due to advances in structural determination and computational methods. In this scenario, data-intensive cavity analysis demands efficient scripting routines built on easily manipulated data structures. To fulfill this need, we developed pyKVFinder, a Python package to detect and characterize cavities in biomolecular structures for data science and automated pipelines. RESULTS: pyKVFinder efficiently detects cavities in biomolecular structures and computes their volume, area, depth and hydropathy, storing these cavity properties in NumPy arrays. Benefited from Python ecosystem interoperability and data structures, pyKVFinder can be integrated with third-party scientific packages and libraries for mathematical calculations, machine learning and 3D visualization in automated workflows. As proof of pyKVFinder's capabilities, we successfully identified and compared ADRP substrate-binding site of SARS-CoV-2 and a set of homologous proteins with pyKVFinder, showing its integrability with data science packages such as matplotlib, NGL Viewer, SciPy and Jupyter notebook. CONCLUSIONS: We introduce an efficient, highly versatile and easily integrable software for detecting and characterizing biomolecular cavities in data science applications and automated protocols. pyKVFinder facilitates biostructural data analysis with scripting routines in the Python ecosystem and can be building blocks for data science and drug design applications.

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This paper presents a biomimetic prototype of a mobile robot that can be used to inspect the subdrainage conditions of pipelines located along different highways in Mexico. Computer-aided design tools have been used to size each of the prototype components as inspired by anatomical spider structure. Springs are integrated to generate proper contact pressure against the pipe walls. The robot locomotion system is implemented with adaptable behaviour for the irregularities of pipelines along its journey. The robot prototype is manufactured in 3D printing with the advantage of having its spare parts easily replaceable. Reported results show internal pipe status through a mini video camera on the top of the robot.

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The dataset presented in this article was collected in a laboratory flow circuit, which was designed to investigate high-viscosity flows. The data set is composed of 1200 s (equivalent to 12,000 samples) of mass flow and pressure measurements taken at five points along the pipeline. The first 300 s were recorded when the flow in the loop was composed only of glycerol. The remaining data were acquired when the flow was composed of a water-glycerol mixture. During the data acquisition, two extractions were produced. The research reported in [1] uses 160 s of the data provided here. This article explains in detail the experimental set-up and the principal instruments used for obtaining the dataset. The dataset is in the form of seven columns: Time, Mass Flow, Pressure 1, Pressure 2, Pressure 3, Pressure 4, Pressure 5, in supplementary Excel and Matlab files.