66 research outputs found

    Large-scale unit commitment under uncertainty: an updated literature survey

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    The Unit Commitment problem in energy management aims at finding the optimal production schedule of a set of generation units, while meeting various system-wide constraints. It has always been a large-scale, non-convex, difficult problem, especially in view of the fact that, due to operational requirements, it has to be solved in an unreasonably small time for its size. Recently, growing renewable energy shares have strongly increased the level of uncertainty in the system, making the (ideal) Unit Commitment model a large-scale, non-convex and uncertain (stochastic, robust, chance-constrained) program. We provide a survey of the literature on methods for the Uncertain Unit Commitment problem, in all its variants. We start with a review of the main contributions on solution methods for the deterministic versions of the problem, focussing on those based on mathematical programming techniques that are more relevant for the uncertain versions of the problem. We then present and categorize the approaches to the latter, while providing entry points to the relevant literature on optimization under uncertainty. This is an updated version of the paper "Large-scale Unit Commitment under uncertainty: a literature survey" that appeared in 4OR 13(2), 115--171 (2015); this version has over 170 more citations, most of which appeared in the last three years, proving how fast the literature on uncertain Unit Commitment evolves, and therefore the interest in this subject

    Expression and pharmacological inhibition of TrkB and EGFR in glioblastoma

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    A member of the Trk family of neurotrophin receptors, tropomyosin receptor kinase B (TrkB, encoded by the NTRK2 gene) is an increasingly important target in various cancer types, including glioblastoma (GBM). EGFR is among the most frequently altered oncogenes in GBM, and EGFR inhibition has been tested as an experimental therapy. Functional interactions between EGFR and TrkB have been demonstrated. In the present study, we investigated the role of TrkB and EGFR, and their interactions, in GBM. Analyses of NTRK2 and EGFR gene expression from The Cancer Genome Atlas (TCGA) datasets showed an increase in NTRK2 expression in the proneural subtype of GBM, and a strong correlation between NTRK2 and EGFR expression in glioma CpG island methylator phenotype (G-CIMP+) samples. We showed that when TrkB and EGFR inhibitors were combined, the inhibitory effect on A172 human GBM cells was more pronounced than when either inhibitor was given alone. When U87MG GBM cells were xenografted into the flank of nude mice, tumor growth was delayed by treatment with TrkB and EGFR inhibitors, given alone or combined, only at specific time points. Intracranial GBM growth in mice was not significantly affected by drug treatments. Our findings indicate that correlations between NTRK2 and EGFR expression occur in specific GBM subgroups. Also, our results using cultured cells suggest for the first time the potential of combining TrkB and EGFR inhibition for the treatment of GBM

    EPIDEMIOLOGY OF PARACOCCIDIOIDOMYCOSIS

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    SUMMARYThe epidemiological characteristics of paracoccidioidomycosis were reviewed and updated. The new endemic areas in Brazil were discussed in the section regarding the geographic distribution of the mycosis. Subclinical infection with Paracoccidioides brasiliensis was discussed on the basis of skin test surveys with antigens of the fungus, seroepidemiological studies, and disease cases outside Latin America. Large case series permitted a comparison of the prevalence of the mycosis in different regions, its estimated incidence and risk factors for the development of the disease. Aspects modulating the expression of the clinical forms of paracoccidioidomycosis are also presented. This review also deals with diseases associated with the mycosis, opportunistic paracoccidioidomycosis, lethality, mortality and infection and disease in animals

    Consistent patterns of common species across tropical tree communities

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    Trees structure the Earth’s most biodiverse ecosystem, tropical forests. The vast number of tree species presents a formidable challenge to understanding these forests, including their response to environmental change, as very little is known about most tropical tree species. A focus on the common species may circumvent this challenge. Here we investigate abundance patterns of common tree species using inventory data on 1,003,805 trees with trunk diameters of at least 10 cm across 1,568 locations 1–6 in closed-canopy, structurally intact old-growth tropical forests in Africa, Amazonia and Southeast Asia. We estimate that 2.2%, 2.2% and 2.3% of species comprise 50% of the tropical trees in these regions, respectively. Extrapolating across all closed-canopy tropical forests, we estimate that just 1,053 species comprise half of Earth’s 800 billion tropical trees with trunk diameters of at least 10 cm. Despite differing biogeographic, climatic and anthropogenic histories 7, we find notably consistent patterns of common species and species abundance distributions across the continents. This suggests that fundamental mechanisms of tree community assembly may apply to all tropical forests. Resampling analyses show that the most common species are likely to belong to a manageable list of known species, enabling targeted efforts to understand their ecology. Although they do not detract from the importance of rare species, our results open new opportunities to understand the world’s most diverse forests, including modelling their response to environmental change, by focusing on the common species that constitute the majority of their trees
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