Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time, and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space. While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes, vast areas of the tropics remain understudied. In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity, but it remains among the least known forests in America and is often underrepresented in biodiversity databases. To worsen this situation, human-induced modifications may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge, it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

As bases históricas da gestão da qualidade: a abordagem clássica da administração e seu impacto na moderna gestão da qualidade The historical principles of quality management: the classical management approach and its impact on modern quality management

Este artigo mostra como a Gestão da Qualidade, tal qual conhecemos hoje, embasou seu desenvolvimento em escolas fundamentais da Administração. Em particular, enfoca-se aqui a Escola Clássica, suas identidades e confrontos com a Gestão da Qualidade e seus reflexos nas suas principais ferramentas. Esta análise permite entender o verdadeiro alcance de conceitos e estratégias da Gestão da Qualidade, garantindo assim sua correta aplicação.<br>This paper shows how Quality Management, as we understand it today, has used the main concepts of fundamental management approaches. Here the impact of Classical Management Theory on Quality Management is considered. This analysis allows us to understand correctly the main concepts of Quality Management, as well as its main tools, in order to guarantee their correct application

The ATLAS Simulation Infrastructure

The simulation software for the ATLAS Experiment at the Large Hadron Collider is being used for large-scale production of events on the LHC Computing Grid. This simulation requires many components, from the generators that simulate particle collisions, through packages simulating the response of the various detectors and triggers. All of these components come together under the ATLAS simulation infrastructure. In this paper, that infrastructure is discussed, including that supporting the detector description, interfacing the event generation, and combining the GEANT4 simulation of the response of the individual detectors. Also described are the tools allowing the software validation, performance testing, and the validation of the simulated output against known physics processes. © 2010 CERN for the benefit of the ATLAS collaboration

Commissioning of the ATLAS Muon Spectrometer with cosmic rays

The ATLAS detector at the Large Hadron Collider has collected several hundred million cosmic ray events during 2008 and 2009. These data were used to commission the Muon Spectrometer and to study the performance of the trigger and tracking chambers, their alignment, the detector control system, the data acquisition and the analysis programs. We present the performance in the relevant parameters that determine the quality of the muon measurement. We discuss the single element efficiency, resolution and noise rates, the calibration method of the detector response and of the alignment system, the track reconstruction efficiency and the momentum measurement. The results show that the detector is close to the design performance and that the Muon Spectrometer is ready to detect muons produced in high energy proton-proton collisions. © 2010 CERN for the benefit of the ATLAS collaboration