88 research outputs found

    Optimal Damping Profile for a Heaving Buoy Wave Energy Converter

    Get PDF
    This paper discusses optimal damping profiles for a heaving buoy Wave Energy Converter (WEC) with a single degree of freedom. The goal is to examine how the device can be controlled to harvest maximum energy from incident waves. Both latching and declutching strategies are allowed via a general parametrization of the damping force. Ultimately, the research attempts to determine the best control strategy to apply considering the relative resonant frequency of the device and the monochromatic wave frequency set

    Optimal Damping Profile for a Heaving Buoy Wave Energy Converter

    Get PDF
    This paper discusses optimal damping profiles for a heaving buoy Wave Energy Converter (WEC) with a single degree of freedom. The goal is to examine how the device can be controlled to harvest maximum energy from incident waves. Both latching and declutching strategies are allowed via a general parametrization of the damping force. Ultimately, the research attempts to determine the best control strategy to apply considering the relative resonant frequency of the device and the monochromatic wave frequency set

    Productivity and economic assessment of wave energy projects through operational simulations

    Get PDF
    In this work, we present a methodology for the assessment of the economic value of ocean wave energy schemes. Such an assessment is a necessary tool for supporting investment decisions in the development of wave farms and in the development of wave energy converter (WEC) technology. To overcome the lack of operational experience, the methodology presented includes detailed operational simulations which relate the operational costs and the availability of the plant for power production to the characteristics of the device, the location, and the maintenance strategy chosen. The methodology consists of firstly, a productivity and costs assessment which embodies the operational simulations and secondly, a financial calculator which employs discounted cash-flow techniques to produce selected economic indicators. A case study, consisting of one hundred WECs units deployed off the West Coast of Ireland, is presented to exemplify the use of the methodology. The paper also explores how the key inputs to the assessment affect the economic performance of the case study project via a sensitivity analysis

    A comprehensive assessment of the applicability of available and proposed offshore mooring and foundation technologies and design tools for array applications

    Get PDF
    PublishedThe function and type of mooring and/or foundation system are determined by a number of factors including: cost, site characteristics, expected environmental loading and environmental or legislative constraints. The design of the device and its mode of operation will also influence the decision making process. It is the role of DTOcean Work Package 4 to produce a decision making tool which has the capability to assess a range of technologies for the design and selection of mooring and foundation systems for marine renewable energy (MRE) device arrays. In this first deliverable report, criteria are introduced which can be used to appraise technologies and approaches relevant to MRE devices. Existing mooring and foundation technologies used in the offshore industry are summarised with examples given of MRE device deployments. A general overview of the design tools which are currently used for mooring and foundation design in the offshore and MRE industries is provided, along with a list of the capabilities of several commercially available software packages.European Commission’s 7th Framework; Grant agreement number: 60859

    Advances in the development of dielectric elastomer generators for wave energy conversion

    Get PDF
    This paper presents a summary of recent progress towards the development and upscaling of an emerging class of electrostatic power take-off (PTO) systems for wave energy converters (WECs), called dielectric elastomer generators (DEGs). DEGs are electromechanical devices able to convert mechanical energy into electrical energy by exploiting the deformation of rubber-like dielectric materials. The high power density (in the order of hundreds of Watts per kilogram), good efficiency and ease of assembling, combined with the low-cost of the employed materials (a few euros per kilogram) and their intrinsic resilient/reliable response to mechanical shocks make DEGs a very promising option for the deployment of a future generation of WECs. In the last decade, some specific concepts of WECs based on DEGs have been devised and a considerable interest in the topic has been aroused in the wave energy community. Among the candidate DEG topologies for wave energy harvesting, recent studies have suggested that a specific layout, namely the axial-symmetric inflating DEG diaphragm, could be a very promising candidate for future upscaling. This paper first describes the operating principle of DEG PTOs and the effect of electro-mechanical material parameters on their energetic performance. With reference to the above-mentioned inflating DEG diaphragm topology, an overview of concepts for integration on WECs is then provided, with a special focus on advanced concepts enabling the achievement of dynamical tuning with the incoming waves. A general lumped-parameter modelling approach for the design of DEG-based WECs is proposed. Experimental activity carried out to date, i.e. dry-run laboratory tests, wave-tank tests and preliminary sea trials is reviewed, with the aim of showing the progression in the device's scale and performance. Finally, economical and technological considerations are outlined, in order to point out challenges, future research opportunities and to draft a roadmap for future research and technological transfer

    Predictive modelling of a novel anti-adhesion therapy to combat bacterial colonisation of burn wounds

    Get PDF
    As the development of new classes of antibiotics slows, bacterial resistance to existing antibiotics is becoming an increasing problem. A potential solution is to develop treatment strategies with an alternative mode of action. We consider one such strategy: anti-adhesion therapy. Whereas antibiotics act directly upon bacteria, either killing them or inhibiting their growth, anti-adhesion therapy impedes the binding of bacteria to host cells. This prevents bacteria from deploying their arsenal of virulence mechanisms, while simultaneously rendering them more susceptible to natural and artificial clearance. In this paper, we consider a particular form of anti-adhesion therapy, involving biomimetic multivalent adhesion molecule 7 coupled polystyrene microbeads, which competitively inhibit the binding of bacteria to host cells. We develop a mathematical model, formulated as a system of ordinary differential equations, to describe inhibitor treatment of a Pseudomonas aeruginosa burn wound infection in the rat. Benchmarking our model against in vivo data from an ongoing experimental programme, we use the model to explain bacteria population dynamics and to predict the efficacy of a range of treatment strategies, with the aim of improving treatment outcome. The model consists of two physical compartments: the host cells and the exudate. It is found that, when effective in reducing the bacterial burden, inhibitor treatment operates both by preventing bacteria from binding to the host cells and by reducing the flux of daughter cells from the host cells into the exudate. Our model predicts that inhibitor treatment cannot eliminate the bacterial burden when used in isolation; however, when combined with regular or continuous debridement of the exudate, elimination is theoretically possible. Lastly, we present ways to improve therapeutic efficacy, as predicted by our mathematical model

    Screening for multi-drug-resistant Gram-negative bacteria: what is effective and justifiable?

    Get PDF
    Effectiveness is a key criterion in assessing the justification of antibiotic resistance interventions. Depending on an intervention's effectiveness, burdens and costs will be more or less justified, which is especially important for large scale population-level interventions with high running costs and pronounced risks to individuals in terms of wellbeing, integrity and autonomy. In this paper, we assess the case of routine hospital screening for multi-drug-resistant Gram-negative bacteria (MDRGN) from this perspective. Utilizing a comparison to screening programs for Methicillin-Resistant Staphylococcus aureus (MRSA) we argue that current screening programmes for MDRGN in low endemic settings should be reconsidered, as its effectiveness is in doubt, while general downsides to screening programs remain. To accomplish justifiable antibiotic stewardship, MDRGN screening should not be viewed as a separate measure, but rather as part of a comprehensive approach. The program should be redesigned to focus on those at risk of developing symptomatic infections with MDRGN rather than merely detecting those colonised

    Colo-Pro: a pilot randomised controlled trial to compare standard bolus-dosed cefuroxime prophylaxis to bolus-continuous infusion–dosed cefuroxime prophylaxis for the prevention of infections after colorectal surgery

    Get PDF
    Standard bolus-dosed antibiotic prophylaxis may not inhibit growth of antibiotic resistant colonic bacteria, a cause of SSIs after colorectal surgery. An alternative strategy is continuous administration of antibiotic throughout surgery, maintaining concentrations of antibiotics that inhibit growth of resistant bacteria. This study is a pilot comparing bolus-continuous infusion with bolus-dosed cefuroxime prophylaxis in colorectal surgery. This is a pilot randomised controlled trial in which participants received cefuroxime bolus-infusion (intervention arm) targeting free serum cefuroxime concentrations of 64 mg/L, or 1.5 g cefuroxime as a bolus dose four-hourly (standard arm). Patients in both arms received metronidazole (500 mg intravenously). Eligible participants were adults undergoing colorectal surgery expected to last for over 2 h. Results were analysed on an intention-to-treat basis. The study was successfully piloted, with 46% (90/196) of eligible patients recruited and 89% (80/90) of participants completing all components of the protocol. A trialled bolus-continuous dosing regimen was successful in maintaining free serum cefuroxime concentrations of 64 mg/L. No serious adverse reactions were identified. Rates of SSIs (superficial and deep SSIs) were lower in the intervention arm than the standard treatment arm (24% (10/42) vs. 30% (13/43)), as were infection within 30 days of operation (41% (17/43) vs 51% (22/43)) and urinary tract infections (2% (1/42) vs. 9% (4/43)). These infection rates can be used to power future clinical trials. This study demonstrates the feasibility of cefuroxime bolus-continuous infusion of antibiotic prophylaxis trials, and provides safety data for infusions targeting free serum cefuroxime concentrations of 64 mg/L. Trial registration: NCT02445859

    A membrane computing simulator of trans-hierarchical antibiotic resistance evolution dynamics in nested ecological compartments (ARES)

    Get PDF
    In this article, we introduce ARES (Antibiotic Resistance Evolution Simulator) a software device that simulates P-system model scenarios with five types of nested computing membranes oriented to emulate a hierarchy of eco-biological compartments, i.e. a) peripheral ecosystem; b) local environment; c) reservoir of supplies; d) animal host; and e) host's associated bacterial organisms (microbiome). Computational objects emulating molecular entities such as plasmids, antibiotic resistance genes, antimicrobials, and/or other substances can be introduced into this framework and may interact and evolve together with the membranes, according to a set of pre-established rules and specifications. ARES has been implemented as an online server and offers additional tools for storage and model editing and downstream analysisThis work has also been supported by grants BFU2012-39816-C02-01 (co-financed by FEDER funds and the Ministry of Economy and Competitiveness, Spain) to AL and Prometeo/2009/092 (Ministry of Education, Government of Valencia, Spain) and Explora Ciencia y Explora Tecnologia/SAF2013-49788-EXP (Spanish Ministry of Economy and Competitiveness) to AM. IRF is recipient of a "Sara Borrell" postdoctoral fellowship (Ref. CD12/00492) from the Ministry of Economy and Competitiveness (Spain). We are also grateful to the Spanish Network for the Study of Plasmids and Extrachromosomal Elements (REDEEX) for encouraging and funding cooperation among Spanish microbiologists working on the biology of mobile genetic elements (Spanish Ministry of Science and Innovation, reference number BFU2011-14145-E).Campos Frances, M.; Llorens, C.; Sempere Luna, JM.; Futami, R.; Rodríguez, I.; Carrasco, P.; Capilla, R.... (2015). A membrane computing simulator of trans-hierarchical antibiotic resistance evolution dynamics in nested ecological compartments (ARES). Biology Direct. 10(41):1-13. https://doi.org/10.1186/s13062-015-0070-9S1131041Baquero F, Coque TM, Canton R. Counteracting antibiotic resistance: breaking barriers among antibacterial strategies. Expert Opin Ther Targets. 2014;18:851–61.Baquero F, Lanza VF, Canton R, Coque TM. Public health evolutionary biology of antimicrobial resistance: priorities for intervention. Evol Appl. 2014;8:223–39.Baquero F, Coque TM, de la Cruz F. Ecology and evolution as targets: the need for novel eco-evo drugs and strategies to fight antibiotic resistance. Antimicrob Agents Chemother. 2011;55:3649–60.Carlet J, Jarlier V, Harbarth S, Voss A, Goossens H, Pittet D, et al. Ready for a world without antibiotics? The pensieres antibiotic resistance call to action. Antimicrob Resist Infect Control. 2012;1:11.Laxminarayan R, Duse A, Wattal C, Zaidi AK, Wertheim HF, Sumpradit N, et al. Antibiotic resistance-the need for global solutions. Lancet Infect Dis. 2013;13:1057–98.G8-Science-Ministers-Statement. 2013. https://www.gov.uk/government/news/g8-science-ministers-statement .Levy SB, Marshall B. Antibacterial resistance worldwide: causes, challenges and responses. Nat Med. 2004;10:S122–9.Wellington EM, Boxall AB, Cross P, Feil EJ, Gaze WH, Hawkey PM, et al. The role of the natural environment in the emergence of antibiotic resistance in gram-negative bacteria. Lancet Infect Dis. 2013;13:155–65.Marshall BM, Levy SB. Food animals and antimicrobials: impacts on human health. Clin Microbiol Rev. 2011;24:718–33.Marshall BM, Ochieng DJ, Levy SB. Commensals: underappreciated reservoir of antibiotic resistance. Microbe. 2009;4:231–8.Forsberg KJ, Reyes A, Wang B, Selleck EM, Sommer MO, Dantas G. The shared antibiotic resistome of soil bacteria and human pathogens. Science. 2012;337:1107–11.Heuer H, Schmitt H, Smalla K. Antibiotic resistance gene spread due to manure application on agricultural fields. Curr Opin Microbiol. 2011;14:236–43.Teillant A, Laxminarayan R. Economics of Antibiotic Use in U.S. Swine and Poultry Production. Choices. 2015;30:1. 1st Quarter 2015.ANTIBIOTIC RESISTANCE THREATS in the United States. http://www.cdc.gov/drugresistance/threat-report-2013/pdf/ar-threats-2013-508.pdf .Gillings MR. Evolutionary consequences of antibiotic use for the resistome, mobilome and microbial pangenome. Front Microbiol. 2013;4:4.Davies J, Davies D. Origins and evolution of antibiotic resistance. Microbiol Mol Biol Rev. 2010;74:417–33.Palmer AC, Kishony R. Understanding, predicting and manipulating the genotypic evolution of antibiotic resistance. Nat Rev Genet. 2013;14:243–8.Baquero F, Tedim AP, Coque TM. Antibiotic resistance shaping multi-level population biology of bacteria. Front Microbiol. 2013;4:15.Partridge SR. Analysis of antibiotic resistance regions in Gram-negative bacteria. FEMS Microbiol Rev. 2011;35:820–55.Baquero F, Coque TM. Multilevel population genetics in antibiotic resistance. FEMS Microbiol Rev. 2011;35:705–6.Martinez JL, Baquero F, Andersson DI. Predicting antibiotic resistance. Nat Rev Microbiol. 2007;5:958–65.Martinez JL, Baquero F. Emergence and spread of antibiotic resistance: setting a parameter space. Upsala Journal of Medical Sciences. Upsala J Med Sci. 2014, Early Online: 1–10, doi: 10.3109/03009734.2014.901444 ).Baquero F, Nombela C. The microbiome as a human organ. Clin Microbiol Infect. 2012;18 Suppl 4:2–4.Kumsa B, Socolovschi C, Parola P, Rolain JM, Raoult D. Molecular detection of Acinetobacter species in lice and keds of domestic animals in Oromia Regional State. Ethiopia PLoS One. 2012;7:e52377.Ahmad A, Ghosh A, Schal C, Zurek L. Insects in confined swine operations carry a large antibiotic resistant and potentially virulent enterococcal community. BMC Microbiol. 2011;11:23.Graczyk TK, Knight R, Gilman RH, Cranfield MR. The role of non-biting flies in the epidemiology of human infectious diseases. Microbes Infect. 2001;3:231–5.Limoee M, Enayati AA, Khassi K, Salimi M, Ladonni H. Insecticide resistance and synergism of three field-collected strains of the German cockroach Blattella germanica (L.) (Dictyoptera: Blattellidae) from hospitals in Kermanshah, Iran. Trop Biomed. 2011;28:111–8.Salehzadeha A, Tavacolb P, Mahjubc H. Bacterial, fungal and parasitic contamination of cockroaches in public hospitals of Hamadan, Iran. J Vect Borne Dis. 2007;44:105–10.Akinjogunla OJ, Odeyemi AT, Udoinyang EP. Cockroaches (periplaneta americana and blattella germanica): reservoirs of multi drug resistant (MDR) bacteria in Uyo, Akwa Ibom State. Scientific J Biol Sci. 2012;1:19–30.Mideo N, Alizon S, Day T. Linking within- and between-host dynamics in the evolutionary epidemiology of infectious diseases. Trends Ecol Evol. 2008;23:511–7.Gillings MR, Stokes HW. Are humans increasing bacterial evolvability? Trends EcolEvol. 2012;27:346–52.Baquero F. Environmental stress and evolvability in microbial systems. Clin Microbiol Infect. 2009;15 Suppl 1:5–10.Paun G, Rozemberg G, Salomaa A. The Oxford Handbook of Membrane Computing. Oxford, London. Oxford University Press. 2010.Paun G. Membrane Computing. An Introduction. Berlin, Heidelberg. Springer-Verlag GmbH. 2002.Paun G. Computing with membranes. J Comput Syst Sci. 2000;61:108–43.Fontana F, Biancom L, Manca V. P systems and the modeling of biochemical oscillations. Lect Notes Comput Sci. 2006;3850:199–208.Cheruku S, Paun A, Romero-Campero FJ, Perez-Jimenez MJ, Ibarra OH. Simulating FAS-induced apoptosis by using P systems. Prog Nat Sci. 2007;4:424–31.Perez-Jimenez MJ, Romero-Campero FJ. P systems, a new computational modelling tool for systems biology. Transactions on computational systems. Lect N Bioinformat. 2006;Biology VI:176–97.Romero-Campero FJ, Perez-Jimenez MJ. Modelling gene expression control using P systems: The Lac Operon, a case study. Biosystems. 2008;91:438–57.Romero-Campero FJ, Perez-Jimenez MJ. A model of the quorum sensing system in Vibrio fischeri using P systems. Artif Life. 2008;14:95–109.Besozzi D, Cazzaniga P, Pescini D, Mauri G. Modelling metapopulations with stochastic membrane systems. Biosystems. 2008;91:499–514.Cardona M, Colomer MA, Perez-Jimenez MJ, Sanuy D, Margalida A. Modelling ecosystems using P Systems: The Bearded Vulture, a case of study. Lect Notes Comput Sci. 2009;5391:137–56.Cardona M, Colomer MA, Margalida A, Perez-Hurtado I, Perez-Jimenez MJ, Sanuy D. A P system based model of an ecosystem of some scavenger birds. Lect Notes Comput Sci. 2010;5957:182–95.Frisco P, Gheorghe M, Perez-Jimenez M. Applications of Membrane Computing in Systems and Synthetic biology. Cham. Springer International Publishing. 2014.Membrane Computing Community. http://ppage.psystems.eu .P-Lingua. http://www.p-lingua.org/wiki/index.php/Main_Page .Llorens C, Futami R, Covelli L, Dominguez-Escriba L, Viu JM, Tamarit D, et al. The Gypsy Database (GyDB) of mobile genetic elements: release 2.0. Nucleic Acids Res. 2011;39:D70–4.Baquero F. From pieces to patterns: evolutionary engineering in bacterial pathogens. Nat Rev Microbiol. 2004;2:510–8.Java. http://www.java.com .Garcia-Quismondo M, Gutierrez-Escudero R, Martinez-del-Amor MA, Orejuela-Pinedo E, Pérez-Hurtado I. P-Lingua 2.0: a software framework for cell-like P systems. Int J Comput Commun. 2009;IV:234.R programming language. http://www.r-project.org .Maciel A, Sankaranarayanan G, Halic T, Arikatla VS, Lu Z, De S. Surgical model-view-controller simulation software framework for local and collaborative applications. Int J Comput Assist Radiol Surg. 2011;6:457–71.Dethlefsen L, McFall-Ngai M, Relman DA. An ecological and evolutionary perspective on human-microbe mutualism and disease. Nature. 2007;449:811–8.Ley RE, Lozupone CA, Hamady M, Knight R, Gordon JI. Worlds within worlds: evolution of the vertebrate gut microbiota. Nat Rev Microbiol. 2008;6:776–88.Pallen MJ, Wren BW. Bacterial pathogenomics. Nature. 2007;449:835–42.Carrasco P, Perez-Cobas AE, Van de Pol C, Baixeras J, Moya A, Latorre A. Succession of the gut microbiota in the cockroach Blattella germanica. Int Microbiol. 2014;17:99–109
    corecore