International audienceThis study analyzed the crustacean diversity, distribution and relationship with environmental factors in the western and the southern Portuguese continental shelf, between 10 and 200 m depth. A total of 10,639 specimens belonging to 242 taxa from 90 families were identified, mostly amphipods (55.8% of the total taxa). The mysid Gastrosaccus spinifer and the amphipods Socarnes erythrophthalmus and Cheirocratus sundevallii were the most abundant and the amphipods Ampelisca brevicornis, Leucothoe incisa and Autonoe spiniventris were the most frequent species. The highest abundance and diversity was found in coarser sediments with up to 306 individuals per 0.1 m2. Alpha diversity ranged from 1 to 28 sp./0.1 m2. Moreover, this study confirmed six previously doubtful first records and added an additional 19 new records to the Portuguese fauna. The results also confirmed the Portuguese coast as a transition zone of mixed Atlantic and Mediterranean faunas and exposed a noticeable North African and Macaronesian influence. A multivariate analysis based on the abundance of crustaceans revealed six affinity groups characterized by: (a) C. sundevallii, Guernea (Guernea) coalita and Sarsinebalia cristoboi on very coarse sands; (b) G. spinifer, Nototropis falcatus and Pontocrates arenarius on coarse sands; (c) Othomaera othonis, Processa modica modica and Animoceradocus semiserratus on heterogeneous medium sands; (d) A. brevicornis, Urothoe pulchella and Necalianassa truncata on fine sands; (e) Ampelisca pectenata, Bodotria scorpioides and Astacilla dilatata on heterogeneous fine sands and (f) Callianassa subterranea, Ampelisca tenuicornis and Ampelisca typica on muddy fine sands. Sediment grain-size and depth were the variables best related to the benthic crustacean spatial distribution patterns along the Portuguese continental shelf
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A multi-product mathematical model for iron ore stockyard planning problem Um modelo matemático multiprodutos para o problema de planejamento de meios de ferro
This paper proposes a methodology for the optimized location and sizing of capacitor banks in distribution networks. The variabilities of system load and grid configuration are both considered. Cluster analysis on daily load curves is employed to model the load variability adequately, while changes in the grid configuration concern feeders' reconfigurations associated with load transfers among them. Voltage profile improvement, energy loss reduction, and minimization of installation costs are pursued objectives, selected here for planning the investment in capacitor banks. The problem is combinatorial in nature and its solution using a genetic algorithm is proposed. Tests with a real distribution system are performed, exploring the knowledge about common network switching operations and employing system loading measurement data. The obtained results show the importance of adequately considering, during the planning phase, loading and topological conditions to which the distribution system will be submitted during operation.
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