SAND FLY SPECIES COMPOSITION (DIPTERA: PSYCHODIDAE: PHLEBOTOMINAE) IN THE MUNICIPALITY OF CANTAGALO , AN AREA WITH SPORADIC CASES OF HUMAN CUTANEOUS LEISHMANIASIS IN RIO DE JANEIRO STATE, BRAZIL

SUMMARY The municipality of Cantagalo is an area with sustained transmission of American Cutaneous Leishmaniasis (ACL). Monthly sand fly collections were performed for three years (June 2012 - May 2015) using a CDC light trap. A total of 3,310 specimens belonging to 12 species were trapped: Nyssomyia intermedia, Nyssomyia whitmani, Migonemyia migonei, Evandromyia lenti, Evandromyia cortelezzii, Micropygomyia quinquefer, Brumptomyia brumpti, Psathyromyia aragaoi, Micropygomyia schreiberi, Pintomyia fischeri, Sciopemyia sordellii, and Evandromyia edwardsi. The last seven species have not been previously recorded in this area. The highest abundance of species occurred between October and March. October was the month with the highest number of captured sand flies, one month before the peak in the summer rainfall. In October the highest number of Ny. intermedia, Ny. whitmani and Mg. migonei, were also collected, the three epidemiologically most important species. The high abundance of species with epidemiological importance for ACL transmission might explain the sporadic occurrence of the disease in the area

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

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