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The Climate Science for Service Partnership Brazil (CSSP-Brazil) project provides Brazil and UK partners the opportunity to address important challenges faced by the climate modeling community, including the need to develop subseasonal and seasonal prediction and climate projection services. This paper provides an overview of the climate modeling and prediction research conducted through CSSP-Brazil within the context of a framework to advance climate prediction services in Brazil that includes a research-to-services (R2S) and a services-to-research (S2R) feedback pathway. The paper also highlights plans to advance scientific understanding and capability to produce beneficial climate knowledge and new products to improve climate prediction services to support decisions in various industries in Brazil. Policy-relevant outcomes from climate modeling and prediction exercises illustrated in this paper include supporting stakeholders with climate information provided from weeks to months ahead for (a) improving water management strategies for human consumption, navigation, and agricultural and electricity production; (b) defining crop variety and calendars for food production; and (c) diversifying energy production with alternatives to hydropower.

We introduce a trusted infrastructure for the symbolic analysis of modern event-driven Web applications. This infrastructure consists of reference implementations of the DOM Core Level 1, DOM UI Events, JavaScript Promises and the JavaScript async/await APIs, all underpinned by a simple Core Event Semantics which is sufficiently expressive to describe the event models underlying these APIs. Our reference implementations are trustworthy in that three follow the appropriate standards line-by-line and all are thoroughly tested against the official test-suites, passing all the applicable tests. Using the Core Event Semantics and the reference implementations, we develop JaVerT.Click, a symbolic execution tool for JavaScript that, for the first time, supports reasoning about JavaScript programs that use multiple event-related APIs. We demonstrate the viability of JaVerT.Click by proving both the presence and absence of bugs in real-world JavaScript code., LIPIcs, Vol. 166, 34th European Conference on Object-Oriented Programming (ECOOP 2020), pages 28:1-28:29

The aim of this work was to evaluate the influence of the type of polymer and the effect of drying on the stability of lycopene-rich beads obtained by ionic gelation of a watermelon concentrate. Sodium alginate and pectin were used as polymers for encapsulation. The wet and the dried beads were characterized for lycopene retention when exposed to different thermal treatments (60 °C and 90 °C) and pHs (2, 5 and 8), as well as for particle size distribution, morphology and thermogravimetric analysis. All the particles showed high lycopene protection against the evaluated conditions of temperature and pH. Storage stability at different temperatures was also evaluated. The wet beads produced with alginate and pectin showed lycopene retention of 29 and 21%, respectively, after 8 weeks of refrigerated storage, while the dried beads were showed retentions higher than 80% above 25 °C. Ionic gelation showed to be a promising alternative to obtain stable lycopene-rich dried ingredients. Made available in DSpace on 2022-05-18T11:13:16Z (GMT). No. of bitstreams: 1 2019-SAMPAIO-et-al.-2019.pdf: 1553162 bytes, checksum: 2181fadfdd390151e59647f2765fc550 (MD5) Previous issue date: 2019

We propose a novel, unified approach to the development of compositional symbolic execution tools, bridging the gap between classical symbolic execution and compositional program reasoning based on separation logic. Using this approach, we build JaVerT 2.0, a symbolic analysis tool for JavaScript that follows the language semantics without simplifications. JaVerT 2.0 supports whole-program symbolic testing, verification, and, for the first time, automatic compositional testing based on bi-abduction. The meta-theory underpinning JaVerT 2.0 is developed modularly, streamlining the proofs and informing the implementation. Our explicit treatment of symbolic execution errors allows us to give meaningful feedback to the developer during whole-program symbolic testing and guides the inference of resource of the bi-abductive execution. We evaluate the performance of JaVerT 2.0 on a number of JavaScript data-structure libraries, demonstrating: the scalability of our whole-program symbolic testing; an improvement over the state-of-the-art in JavaScript verification; and the feasibility of automatic compositional testing for JavaScript.

Made available in DSpace on 2018-10-20T00:38:19Z (GMT). No. of bitstreams: 1 DissertacaoFinalcapaduraGessicaLira.pdf: 2427959 bytes, checksum: af74834d20d237f10ba7558f7e34fd7f (MD5) Previous issue date: 2018-08-27 Dissertação (Mestrado em Ciências de Alimentos) - Universidade Federal do Rio de Janeiro, Instituto de Química. Orientadoras: Renata Valeriano Tonon (CTAA), Flávia dos Santos Gomes (CTAA).