Making gas-CCS a commercial reality: The challenges of scaling up

Significant reductions in CO2 emissions are required to limit the global temperature rise to 2°C. Carbon capture and storage (CCS) is a key enabling technology that can be applied to power generation and industrial processes to lower their carbon intensity. There are, however, several challenges that such a method of decarbonization poses when used in the context of natural gas (gas-CCS), especially for solvent-based (predominantly amines) post-combustion capture. These are related to: (i) the low CO2 partial pressure of the exhaust gases from gas-fired power plants (3-4%vol. CO2), which substantially limits the driving force for the capture process; (ii) their high O2 concentration (12-13%vol. O2), which can degrade the capture media via oxidative solvent degradation; and (iii) their high volumetric flow rates, which means large capture plants are needed. Such post-combustion gas-CCS features unavoidably lead to increased CO2 capture costs. This perspective aims to summarize the key technologies used to overcome these as a priority, including supplementary firing, humidified systems, exhaust gas recirculation and selective exhaust gas recirculation. These focus on the maximum CO2 levels achievable for each, as well as the electrical efficiencies attainable when the capture penalty is taken into account. Oxy-turbine cycles are also discussed as an alternative to post-combustion gas-CCS, indicating the main advantages and limitations of these systems together with the expected electrical efficiencies. Furthermore, we consider the challenges for scaling-up and deployment of these technologies at a commercial level to enable gas-CCS to play a crucial role in a low-carbon future

Developing a Simulation Model for Autonomous Driving Education in the Robobo SmartCity Framework

Abstract: This paper focuses on long-term education in Artificial Intelligence (AI) applied to robotics. Specifically, it presents the Robobo SmartCity educational framework. It is based on two main elements: the smartphone-based robot Robobo and a real model of a smart city. We describe the development of a simulation model of Robobo SmartCity in the CoppeliaSim 3D simulator, implementing both the real mock-up and the model of Robobo. In addition, a set of Python libraries that allow teachers and students to use state-of-the-art algorithms in their education projects is described too.Ministerio de Ciencia, Innovación y Universidades of Spain/FEDER; t RTI2018-101114-B-I00 Erasmus+ Programme of the European Union; 2019-1-ES01-KA201-065742, Centro de Investigación de Galicia “CITIC”; ED431G 2019/01

Analysis of virus genomes from glacial environments reveals novel virus groups with unusual host interactions

Microbial communities in glacial ecosystems are diverse, active, and subjected to strong viral pressures and infection rates. In this study we analyse putative virus genomes assembled from three dsDNA viromes from cryoconite hole ecosystems of Svalbard and the Greenland Ice Sheet to assess the potential hosts and functional role viruses play in these habitats. We assembled 208 million reads from the virus-size fraction and developed a procedure to select genuine virus scaffolds from cellular contamination. Our curated virus library contained 546 scaffolds up to 230 Kb in length, 54 of which were circular virus consensus genomes. Analysis of virus marker genes revealed a wide range of viruses had been assembled, including bacteriophages, cyanophages, nucleocytoplasmic large DNA viruses and a virophage, with putative hosts identified as Actinobacteria, Alphaproteobacteria, Cyanobacteria, Firmicutes, Gammaproteobacteria, eukaryotic algae and amoebae. Whole genome comparisons revealed the majority of circular genome scaffolds formed 12 novel groups, two of which contained multiple phage members with plasmid-like properties, including a group of phage-plasmids possessing plasmid-like partition genes and toxin-antitoxin addiction modules to ensure their replication and a satellite phage-plasmid group. Surprisingly we also assembled a phage that not only encoded plasmid partition genes, but a clustered regularly interspaced short palindromic repeat (CRISPR)/Cas adaptive bacterial immune system. One of the spacers was an exact match for another phage in our virome, indicating that in a novel use of the system, the lysogen was potentially capable of conferring immunity on its bacterial host against other phage. Together these results suggest that highly novel and diverse groups of viruses are present in glacial environments, some of which utilise very unusual life strategies and genes to control their replication and maintain a long-term relationship with their hosts

The massive star population of the Virgo Cluster galaxy NGC 4535

We analyzed the massive star population of the Virgo Cluster galaxy NGC 4535 using archival Hubble Space Telescope Wide Field Planetary Camera 2 images in filters F555W and F814W, equivalent to Johnson V and Kron-Cousins I. We performed high precision point spread function fitting photometry of 24353 sources including 3762 candidate blue supergiants, 841 candidate yellow supergiants and 370 candidate red supergiants. We estimated the ratio of blue to red supergiants as a decreasing function of galactocentric radius. Using Modules for Experiments in Stellar Astrophysics isochrones at solar metallicity, we defined the luminosity function and estimated the star formation history of the galaxy over the last 60 Myrs. We conducted a variability search in the V and I filters using three variability indexes: the median absolute deviation, the interquartile range and the inverse von-Neumann ratio. This analysis yielded 120 new variable candidates with absolute magnitudes ranging from M$_{V}$ = $-$4 to $-$11 mag. We used the MESA evolutionary tracks at solar metallicity, to classify the variables based on their absolute magnitude and their position on the color-magnitude diagram. Among the new candidate variable sources are eight candidate variable red supergiants, three candidate variable yellow supergiants and one candidate luminous blue variable, which we suggest for follow-up observations.Comment: Accepted by A&A, 7 pages, 7 Tables, 53 figure

Robobo SmartCity: An Autonomous Driving Model for Computational Intelligence Learning through Educational Robotics

© 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.[Abstract]: This paper presents the Robobo SmartCity model, an educational resource to introduce students in Computational Intelligence (CI) topics using educational robotics as the core learning technology. Robobo SmartCity allows educators to train learners in Artificial Intelligence (AI) fundamentals from a feasible and practical perspective, following the recommendations of digital education plans to introduce AI at all educational levels. This resource is based on the Robobo educational robot and an autonomous driving setup. It is made up of a city mockup, simulation models, and programming libraries adapted to the students' skill level. In it, students can be trained in CI topics that support robot autonomy, as computer vision, machine learning, or human-robot interaction, while developing solutions in the motivating and challenging scope of autonomous driving. The main details of this open resource are provided with a set of possible challenges to be faced in it. They are organized in terms of the educational level and students’ skills. The resource has been mainly tested with secondary and high school students, obtaining successful learning outcomes, presented here to inspire other teachers in taking advantage of this learning technology in their classes.Xunta de Galicia; ED431G 2019/01This work has been partially funded by the Erasmus+ Programme of the European Union through grant number 2019-1-ES01-KA201-065742, and the Centro de Investigación de Galicia "CITIC", funded by Xunta de Galicia and the European Union (European Regional Development Fund- Galicia 2014-2020 Program), by grant ED431G 2019/01. In addition, the “Programa de ayudas a la etapa predoctoral” from Xunta de Galicia (Consellería de Cultura, Educación y Universidad) supported this work through Sara Guerreiro’s grant

Flexible genes establish widespread bacteriophage pan-genomes in cryoconite hole ecosystems

Bacteriophage genomes rapidly evolve via mutation and horizontal gene transfer to counter evolving bacterial host defenses; such arms race dynamics should lead to divergence between phages from similar, geographically isolated ecosystems. However, near-identical phage genomes can reoccur over large geographical distances and several years apart, conversely suggesting many are stably maintained. Here, we show that phages with near-identical core genomes in distant, discrete aquatic ecosystems maintain diversity by possession of numerous flexible gene modules, where homologous genes present in the pan-genome interchange to create new phage variants. By repeatedly reconstructing the core and flexible regions of phage genomes from different metagenomes, we show a pool of homologous gene variants co-exist for each module in each location, however, the dominant variant shuffles independently in each module. These results suggest that in a natural community, recombination is the largest contributor to phage diversity, allowing a variety of host recognition receptors and genes to counter bacterial defenses to co-exist for each phage

AI curriculum for european high schools: an embedded intelligence approach

Financiado para publicación en acceso aberto: Universidade da Coruña/CISUGXunta de Galicia ; ED431G 2019/0

Sketch Recognition Library Applied for an Image Replication with a Humanoid Robot in a Simulated Environment

This version of the paper has been accepted for publication. The final published paper is available online at: https://doi.org/10.1109/ICMRA51221.2020.9398348.Published in: 2020 3rd International Conference on Mechatronics, Robotics and Automation (ICMRA), Shanghai, China, 16-18 October 2020.[Abstract]: Sketches have been one of the most ancient techniques used by humans to portray their ideas and thoughts. Replicating this ability would help us to better understand the way in which human beings obtain their capabilities. In this work, we implemented an architecture using convolutional neural networks capable of transforming an image to a sequence of strokes to be replicated by a Poppy humanoid robot using inverse kinematic to reproduce the sketches.Thanks for all support of the PARMA group members, the International Cooperation Office, Computer School at Technological Institute of Costa Rica for the internship scholarship provided for the realization of this work. Moreover, the support provided by all people at the Integrated Group of Engineering Research at Universidade da Coruña for all knowledge contributed to this work