On the Informational Comparison of Qualitative Fuzzy Measures

International audienceFuzzy measures or capacities are the most general representation of uncertainty functions. However, this general class has been little explored from the point of view of its information content, when degrees of uncertainty are not supposed to be numerical, and belong to a finite qualitative scale, except in the case of possibility or necessity measures. The thrust of the paper is to define an ordering relation on the set of qualitative capacities expressing the idea that one is more informative than another, in agreement with the possibilistic notion of relative specificity. To this aim, we show that the class of qualitative capacities can be partitioned into equivalence classes of functions containing the same amount of information. They only differ by the underlying epistemic attitude such as pessimism or optimism. A meaningful information ordering between capacities can be defined on the basis of the most pessimistic (resp. optimistic) representatives of their equivalence classes. It is shown that, while qualitative capacities bear strong similarities to belief functions, such an analogy can be misleading when it comes to information content

European Flight Restrictions May Inhibit International Propagation of Ebola

The rise of aviation as the dominant form of international transportation has increased the potential for the spread of infectious diseases. The 2014 West African Ebola Outbreak is no exception, with localized outbreaks in multiple countries caused by infected individuals traveling by plane. To inhibit the spread of Ebola to the United States it has been suggested that airlines cancel direct inbound flights from the affected region. To examine the effects of this approach, we developed and analyzed an agent-based metapopulation network model to simulate the international flight-based spread of Ebola. A metapopulation network consisting of 3,052 subpopulations connected by 83,295 flights was developed to simulate the transportation and infection of individuals in discrete timesteps of 30 minutes. To simulate the transmission dynamics of Ebola within subpopulations, airports, and flights, we constructed an SEIR model in which individuals are classified as either susceptible, exposed, infectious, or removed. The spread of Ebola was simulated using an R0 of 2.1, as estimated for the 2014 West African Ebola outbreak, and extrapolated to scenarios of unilateral flight restrictions. We tested situations in which the United States, the European Union, or other African nations refused inbound flights. We found that flight restrictions can decrease the number of subpopulations with infectious or exposed individuals, with European-bound flight restrictions decreasing the spread of Ebola by as much as 80%. While flight restrictions may be politically and economically infeasible, our model suggests that the implementation of flight restrictions on European-bound flights may effectively mitigate the international spread of Ebola

On the Convergence of Fuzzy Sets and the Completeness of the Space of Fuzzy Sets

AbstractIn this article, we first introduce several convergence concepts of fuzzy sets. Then we construct an embedding of the space of fuzzy sets in a normed linear space. We prove that the space of fuzzy sets is a complete metric space under the embedding. This framework enables us to study the calculus of fuzzy functions

Historic Changes (1941–2008) In Side Channel And Backwater Habitats On An Unchannelized Reach Of The Missouri River

Flow regulation has had pervasive effects on aquatic ecosystems within the world’s large rivers. While channelization on the lower Missouri River has led to major changes in the river and its floodplain, including the loss of shallow water habitats, effects of upstream dams on unchannelized reaches on the Missouri have not been formally assessed. We quantified changes in the number and size of off-channel habitats, specifically backwaters and side channels, on the 95-km unchannelized reach of the Missouri below Gavins Point Dam (Yankton, South Dakota) using historical (1941, 1983–1985, 2008) aerial imagery. Total and mean areas of side channels declined by 77% and 37% and total and mean length decreased by 79% and 42% from 1941 to 2008. Total area of backwaters increased by 40% from 1941 to 2008, whereas mean area decreased by 36%. Our findings suggest that sharp declines in the area and length of side channels have occurred on this unchannelized remnant reach of the Missouri River, with likely significant impacts on aquatic ecosystem processes

Nucleosome instabilities in physiological salt

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Ordered Weighted Average Based Fuzzy Rough Sets

Traditionally, membership to the fuzzy-rough lower, resp. upper approximation is determined by looking only at the worst, resp. best performing object. Consequently, when applied to data analysis problems, these approximations are sensitive to noisy and/or outlying samples. In this paper, we advocate a mitigated approach, in which membership to the lower and upper approximation is determined by means of an aggregation process using ordered weighted average operators. In comparison to the previously introduced vaguely quantified rough set model, which is based on a similar rationale, our proposal has the advantage that the approximations are monotonous w.r.t. the used fuzzy indiscernibility relation. Initial experiments involving a feature selection application confirm the potential of the OWA-based model

Exploring the parameter space of MagLIF implosions using similarity scaling. I. Theoretical framework

Magneto-inertial fusion (MIF) concepts, such as the Magnetized Liner Inertial Fusion (MagLIF) platform [M. R. Gomez et al., Phys. Rev. Lett. 113, 155003 (2014)], constitute a promising path for achieving ignition and significant fusion yields in the laboratory. The space of experimental input parameters defining a MagLIF load is highly multi-dimensional, and the implosion itself is a complex event involving many physical processes. In the first paper of this series, we develop a simplified analytical model that identifies the main physical processes at play during a MagLIF implosion. Using non-dimensional analysis, we determine the most important dimensionless parameters characterizing MagLIF implosions and provide estimates of such parameters using typical fielded or experimentally observed quantities for MagLIF. We then show that MagLIF loads can be "incompletely" similarity scaled, meaning that the experimental input parameters of MagLIF can be varied such that many (but not all) of the dimensionless quantities are conserved. Based on similarity-scaling arguments, we can explore the parameter space of MagLIF loads and estimate the performance of the scaled loads. In the follow-up papers of this series, we test the similar scaling theory for MagLIF loads against simulations for two different scaling "vectors", which include current scaling and rise-time scaling.Comment: 24 pages, submitted to Physics of Plasma

Evidence Propagation and Consensus Formation in Noisy Environments

We study the effectiveness of consensus formation in multi-agent systems where there is both belief updating based on direct evidence and also belief combination between agents. In particular, we consider the scenario in which a population of agents collaborate on the best-of-n problem where the aim is to reach a consensus about which is the best (alternatively, true) state from amongst a set of states, each with a different quality value (or level of evidence). Agents' beliefs are represented within Dempster-Shafer theory by mass functions and we investigate the macro-level properties of four well-known belief combination operators for this multi-agent consensus formation problem: Dempster's rule, Yager's rule, Dubois & Prade's operator and the averaging operator. The convergence properties of the operators are considered and simulation experiments are conducted for different evidence rates and noise levels. Results show that a combination of updating on direct evidence and belief combination between agents results in better consensus to the best state than does evidence updating alone. We also find that in this framework the operators are robust to noise. Broadly, Yager's rule is shown to be the better operator under various parameter values, i.e. convergence to the best state, robustness to noise, and scalability.Comment: 13th international conference on Scalable Uncertainty Managemen

Peroxidase-dependent metabolism of benzene's phenolic metabolites and its potential role in benzene toxicity and carcinogenicity.

The metabolism of two of benzene's phenolic metabolites, phenol and hydroquinone, by peroxidase enzymes has been studied in detail. Studies employing horseradish peroxidase and human myeloperoxidase have shown that in the presence of hydrogen peroxide phenol is converted to 4,4'-diphenoquinone and other covalent binding metabolites, whereas hydroquinone is converted solely to 1,4-benzoquinone. Surprisingly, phenol stimulates the latter conversion rather than inhibiting it, an effect that may play a role in the in vivo myelotoxicity of benzene. Indeed, repeated coadministration of phenol and hydroquinone to B6C3F1 mice results in a dramatic and significant decrease in bone marrow cellularity similar to that observed following benzene exposure. A mechanism of benzene-induced myelotoxicity is therefore proposed in which the accumulation and interaction of phenol and hydroquinone in the bone marrow and the peroxidase-dependent formation of 1,4-benzoquinone are important components. This mechanism may also be responsible, at least in part, for benzene's genotoxic effects, as 1,4-benzoquinone has been shown to damage DNA and is shown here to induce multiple micronuclei in human lymphocytes. Secondary activation of benzene's phenol metabolites in the bone marrow may therefore play an important role in benzene's myelotoxic and carcinogenic effects