The fluorescence detector of the Pierre Auger Observatory

The Pierre Auger Observatory is a hybrid detector for ultra-high energy cosmic rays. It combines a surface array to measure secondary particles at ground level together with a fluorescence detector to measure the development of air showers in the atmosphere above the array. The fluorescence detector comprises 24 large telescopes specialized for measuring the nitrogen fluorescence caused by charged particles of cosmic ray air showers. In this paper we describe the components of the fluorescence detector including its optical system, the design of the camera, the electronics, and the systems for relative and absolute calibration. We also discuss the operation and the monitoring of the detector. Finally, we evaluate the detector performance and precision of shower reconstructions. (C) 2010 Elsevier B.V All rights reserved.

CARBON CREDITS AND ENERGY EFFICIENCY

International carbon credit markets are based in differences between developing and developed countries greenhouse gases emissions mitigation costs and technological limits faced by developed countries. Potential of energy efficiency measures to reduce fossil fuel usage in Brazilian industrial segments is assessed, and analysis of such potentials singles out those segments and regions more apt to generate carbon credits through Clean Development Mechanism (CDM) projects. Though there are currently few Brazilian CDM projects, their number may be significantly increased, which is a positive outcome. For this purpose, it is crucial that energy conservation programs estimate how CDM may improve their economic competitiveness.

Temporal Diversity Patterns and Phenology in Fruit-feeding Butterflies in the Atlantic Forest

The Atlantic Forest deserves special attention due to its high level of species endemism and degree of threat. As in other tropical biomes, there is little information about the ecology of the organisms that occur there. The objectives of this study were to verify how fruit-feeding butterflies are distributed through time, and the relation with meteorological conditions. Species richness and Shannon index were partitioned additively at the monthly level, and beta diversity, used as a hierarchical measure of temporal species turnover, was calculated among months, trimesters, and semesters. Circular analysis was used to verify how butterflies are distributed along seasons and its relation with meteorological conditions. We sampled 6488 individuals of 73 species. Temporal diversity of butterflies was more grouped than expected by chance among the months of each trimester. Circular analyses revealed that diversity is concentrated in hot months (September-March), with the subfamily Brassolinae strongly concentrated in February-March. Average temperature was correlated with total abundance of butterflies, abundance of Biblidinae, Brassolinae and Morphinae, and richness of Satyrinae. The present results show that 3mo of sampling between September and March is enough to produce a nonbiased sample of the local assemblage of butterflies, containing at least 70 percent of the richness and 25 percent of abundance. The influence of temperature on sampling is probably related to butterfly physiology. Moreover, temperature affects resource availability for larvae and adults, which is higher in hot months. The difference in seasonality patterns among subfamilies is probably a consequence of different evolutionary pressures through time.

Slicing the metric space to provide quick indexing of complex data in the main memory

Searching in a dataset for elements that are similar to a given query element is a core problem in applications that manage complex data, and has been aided by metric access methods (MAMs). A growing number of applications require indices that must be built faster and repeatedly, also providing faster response for similarity queries. The increase in the main memory capacity and its lowering costs also motivate using memory-based MAMs. In this paper. we propose the Onion-tree, a new and robust dynamic memory-based MAM that slices the metric space into disjoint subspaces to provide quick indexing of complex data. It introduces three major characteristics: (i) a partitioning method that controls the number of disjoint subspaces generated at each node; (ii) a replacement technique that can change the leaf node pivots in insertion operations; and (iii) range and k-NN extended query algorithms to support the new partitioning method, including a new visit order of the subspaces in k-NN queries. Performance tests with both real-world and synthetic datasets showed that the Onion-tree is very compact. Comparisons of the Onion-tree with the MM-tree and a memory-based version of the Slim-tree showed that the Onion-tree was always faster to build the index. The experiments also showed that the Onion-tree significantly improved range and k-NN query processing performance and was the most efficient MAM, followed by the MM-tree, which in turn outperformed the Slim-tree in almost all the tests. (C) 2010 Elsevier B.V. All rights reserved.

Dendrimer-assisted immobilization of alcohol dehydrogenase in nanostructured films for biosensing: Ethanol detection using electrical capacitance measurements

The selective determination of alcohol molecules either in aqueous solutions or in vapor phase is of great importance for several technological areas. In the last years, a number of researchers have reported the fabrication of highly sensitive sensors for ethanol detection, based upon specific enzymatic reactions occurring at the surface of enzyme-containing electrodes. In this study, the enzyme alcohol dehydrogenase (ADH) was immobilized in a layer-by-layer fashion onto Au-interdigitated electrodes (IDEs), in conjunction with layers of PAMAM dendrimers. The immobilization process was followed in Teal time using quartz crystal microbalance (QCM), indicating that an average mass of 52.1 ng of ADH was adsorbed at each deposition step. Detection was carried out using a novel strategy entirely based upon electrical capacitance measurements, through which ethanol could be detected at concentrations of 1 part per million by volume (ppmv). (C) 2007 Elsevier B.V. All rights reserved.

Formation Mechanism via a Heterocoagulation Approach of FePt Nanoparticles Using the Modified Polyol Process

Herein, we report a new approach of an FePt nanoparticle formation mechanism studying the evolution of particle size and composition during the synthesis using the modified polyol process. One of the factors limiting their application in ultra-high-density magnetic storage media is the particle-to-particle composition, which affects the A1-to-L1(0) transformation as well as their magnetic properties. There are many controversies in the literature concerning the mechanism of the FePt formation, which seems to be the key to understanding the compositional chemical distribution. Our results convincingly show that, initially, Pt nuclei are formed due to reduction of Pt(acac)(2) by the diol, followed by heterocoagulation of Fe cluster species formed from Fe(acac)(3) thermal decomposition onto the Pt nuclei. Complete reduction of heterocoagulated iron species seems to involve a CO-spillover process, in which the Pt nuclei surface acts as a heterogeneous catalyst, leading to the improvement of the single-particle composition control and allowing a much narrower compositional distribution. Our results show significant decreases in the particle-to-particle composition range, improving the A1-to-L1(0) phase transformation and, consequently, the magnetic properties when compared with other reported methods.