495 research outputs found

    Cognitive mapping and multi-criteria analysis for decision aiding: an application to the design of an electric vehicle sharing service

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    The paper presents a model for the design of an electric car sharing service for the city of Milano. Several options of service configurations have been analysed and evaluated according to indicators, to measure the performance of such options in respect to relevant dimensions (i.e., economic and financial costs and revenues, mobility, social benefits, environmental effects). We set up a multicriteria decision analysis, structured by means of cognitive maps. Causal networks to estimate the effects of the options have been identified and instantiated by means of simulation techniques and other qualitative and quantitative models. The focus of the paper is on the development and use of the causal maps and their integration with a multicriteria method. The use of cognitive maps allowed to capture the multiple values of the problem and the value trees of stakeholders objectives. The proposed method can be useful in general for design and planning of mobility service, especially at a strategic level

    Promotion of E-bikes for delivery of goods in European urban areas: an Italian case study

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    The paper presents the first results of some tasks of Pro-E-Bike, an Intelligent Energy Europe (IEE) funded project, started on March 2013 ending in February 2016. Pro-E-Bike promotes clean and energy efficient vehicles, analyses the performance of electric bicycles and electric scooters (Light Electric Vehicle, LEV) for the delivering of goods in urban areas and tests the use of these vehicles in seven European countries with twenty five companies, both delivering ones and companies that deliver their own products. Pilots will enable the demonstration of measurable effects in terms of reduction of CO2 emissions and energy savings in urban transport: related data about environmental, economic and social effects resulted by the introduction of e-bikes and e-scooters in the pilot cities will be collected. The paper will give an overlooks of the Italian pilot, that will take place in Genova, describing the subjects involved and the expected results

    Development of specific PCR assays for the detection of Cryptocaryon irritans

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    Cryptocaryon irritans is one of the most important protozoan pathogens of marine fish, causing the “white spot” disease and posing a significant problem to marine aquaculture. In the present study, a C. irritans-specific reverse primer (S15) was designed based on the published sequence of the second internal transcribed spacer (ITS-2) of ribosomal DNA (rDNA) of C. irritans and used together with the conserved forward primer P1 to develop a specific polymerase chain reaction (PCR) assay for direct, rapid, and specific detection of C. irritans. The specificity of these primers was tested with both closely and distantly related ciliates (Pseudokeroronpsis rubra, Pseudokeroronpsis carnae, Euplotes sp. 1, Ichthyophthirius multifiliis, Pseudourostyla cristata, and Paramecium caudaium), and only C. irritans was detected and no product was amplified from any other ciliates examined in this study using the specific primer set P1-S15. The specific PCR assay was able to detect as low as 45 pg of C. irritans DNA and a nested PCR assay using two primer sets (P1/NC2, P1/S15) increased the sensitivity, allowing the detection of a single C. irritans. The species-specific PCR assays should provide useful tools for the diagnosis, prevention, and molecular epidemiological investigations of C. irritans infection in marine fish

    Evolution of the capsular operon of Streptococcus iniae in response to vaccination

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    Streptococcus iniae causes severe septicemia and meningitis in farmed fish and is also occasionally zoonotic. Vaccination against S. iniae is problematic, with frequent breakdown of protection in vaccinated fish. The major protective antigens in S. iniae are the polysaccharides of the capsule, which are essential for virulence. Capsular biosynthesis is driven and regulated by a 21-kb operon comprising up to 20 genes. In a long-term study, we have sequenced the capsular operon of strains that have been used in autogenous vaccines across Australia and compared it with the capsular operon sequences of strains subsequently isolated from infected vaccinated fish. Intriguingly, strains isolated from vaccinated fish that subsequently become infected have coding mutations that are confined to a limited number of genes in the cps operon, with the remainder of the genes in the operon remaining stable. Mutations in strains in diseased vaccinated fish occur in key genes in the capsular operon that are associated with polysaccharide configuration (cpsG) and with regulation of biosynthesis (cpsD and cpsE). This, along with high ratios of nonsynonymous to synonymous mutations within the cps genes, suggests that immune response directed predominantly against capsular polysaccharide may be driving evolution in a very specific set of genes in the operon. From these data, it may be possible to design a simple polyvalent vaccine with a greater operational life span than the current monovalent killed bacterins

    Probably Approximately Knowing

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    Whereas deterministic protocols are typically guaranteed to obtain particular goals of interest, probabilistic protocols typically provide only probabilistic guarantees. This paper initiates an investigation of the interdependence between actions and subjective beliefs of agents in a probabilistic setting. In particular, we study what probabilistic beliefs an agent should have when performing actions, in a protocol that satisfies a probabilistic constraint of the form: 'Condition C should hold with probability at least p when action a is performed'. Our main result is that the expected degree of an agent's belief in C when it performs a equals the probability that C holds when a is performed. Indeed, if the threshold of the probabilistic constraint should hold with probaility p=1-x^2 for some small value of x then, with probability 1-x, when the agent acts it will assign a probabilistic belief no smaller than 1-x to the possibility that C holds. In other words, viewing strong belief as, intuitively, approximate knowledge, the agent must probably approximately know (PAK-know) that C is true when it acts.Comment: 23 pages, 2 figures, a full version of a paper whose extended abstract appears in the proceeding of PODC 202

    Building collaboration in multi-agent systems using reinforcement learning

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    © Springer Nature Switzerland AG 2018. This paper presents a proof-of concept study for demonstrating the viability of building collaboration among multiple agents through standard Q learning algorithm embedded in particle swarm optimisation. Collaboration is formulated to be achieved among the agents via competition, where the agents are expected to balance their action in such a way that none of them drifts away of the team and none intervene any fellow neighbours territory, either. Particles are devised with Q learning for self training to learn how to act as members of a swarm and how to produce collaborative/collective behaviours. The produced experimental results are supportive to the proposed idea suggesting that a substantive collaboration can be build via proposed learning algorithm
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