Relationships between social forms of organic horticultural production and indicators of environmental quality: a multidimensional approach in Brazil

Organic farming (OF) is increasingly considered as a possible alternative for designing a "new rural" in Brazil, where OF covers a wide range of production and certification systems. However, the ways small farmers adopt OF in green belts to meet an urban demand in organic vegetables have not been extensively investigated. Likewise, the impact of such practices on environmental quality components has not been sufficiently documented. Our objective was to relate forms of organisation to environmental assessment in a watershed where organic horticulture significantly contributes to landscape and water quality. We showed how small farmers were organised or how they organised themselves to meet urban demands and develop OF. We assumed that associated practices were consistent with environmental impacts, as evaluated by indicators. Based on interviews with stakeholders, we identified four forms of organisation and associated farmers' practices. We related them to environmental assessment in three compartments: landscape ecology, water quality and soil quality. Although organisations share some objectives, namely with regard to visual quality and the "right price" of products, differences appear in their scope and internal operation, their values and relationships with consumers, and their technical and environmental contents. As for technical content, input supply, planning processes and crop diversity vary among organisations, ranging from liberal to hierarchical. Our results also showed similarities and differences among various organisations in terms of environmental impact. Such results are interpreted and discussed in the light of technical and social dimensions that account for the progressive design of new systems in Brazil

Modeling Financial Volatility: Extreme Observations, Nonlinearities and Nonstationarities

This paper presents a selective survey of volatility topics, with emphasis on the measurement of volatility and a discussion of some of the most important time series models commonly employed in its modelling. In particular, the paper details the long memory characteristics of volatility, and discusses its possible origins and impact on option pricing. To conclude, the paper discusses statistical tools that discriminate between nonlinearity and nonstationarity.long memory; nonstationarity; nonlinearity; option pricing, volatility

Physics with Beam Tau-Neutrino Appearance at DUNE

We explore the capabilities of the upcoming Deep Underground Neutrino Experiment (DUNE) to measure $\nu_\tau$ charged-current interactions and the associated oscillation probability $P(\nu_\mu \to \nu_\tau)$ at its far detector, concentrating on how such results can be used to probe neutrino properties and interactions. DUNE has the potential to identify significantly more $\nu_\tau$ events than all existing experiments and can use this data sample to nontrivially test the three-massive-neutrinos paradigm by providing complementary measurements to those from the $\nu_e$ appearance and $\nu_\mu$ disappearance channels. We further discuss the sensitivity of the $\nu_\tau$ appearance channel to several hypotheses for the physics that may lurk beyond the three-massive-neutrinos paradigm: a non-unitary lepton mixing matrix, the $3+1$ light neutrinos hypothesis, and the existence of non-standard neutral-current neutrino interactions. Throughout, we also consider the relative benefits of the proposed high-energy tune of the Long-Baseline Neutrino Facility (LBNF) beam-line.Comment: 23 pages, 14 figures, 2 appendice

Mining structured Petri nets for the visualization of process behavior

Visualization is essential for understanding the models obtained by process mining. Clear and efficient visual representations make the embedded information more accessible and analyzable. This work presents a novel approach for generating process models with structural properties that induce visually friendly layouts. Rather than generating a single model that captures all behaviors, a set of Petri net models is delivered, each one covering a subset of traces of the log. The models are mined by extracting slices of labelled transition systems with specific properties from the complete state space produced by the process logs. In most cases, few Petri nets are sufficient to cover a significant part of the behavior produced by the log.Peer ReviewedPostprint (author's final draft