A review of the multicriteria decision analysis applied to oil and gas decommissioning problems

Regardless of the economic activity, decommissioning decisions are often highly complex. This is due to the diversity of operational and local parameters, as well as the multitude of stakeholders involved, who generally have conflicting interests. This sets up a challenging multi-criteria decision problem on the activities to be carried out during the decommissioning process. This paper aims to present an overview of decision-support tools applied to decommissioning, and covers many economic sectors, with a focus on the oil and gas sector and on multi-criteria decision analysis (MCDA) methods. The paper delves deep into the aspects to be considered before reaching a decision, examining the experiences and methods found both in industrial reports and in academic papers

Bottomonium and Drell-Yan production in p-A collisions at 450 GeV

The NA50 Collaboration has measured heavy-quarkonium production in p-A collisions at 450 GeV incident energy (sqrt(s) = 29.1 GeV). We report here results on the production of the Upsilon states and of high-mass Drell-Yan muon pairs (m > 6 GeV). The cross-section at midrapidity and the A-dependence of the measured yields are determined and compared with the results of other fixed-target experiments and with the available theoretical estimates. Finally, we also address some issues concerning the transverse momentum distributions of the measured dimuons.Comment: 18 pages, 9 figures, to be published in Phys. Lett.

J/psi and psi' production and their normal nuclear absorption in proton-nucleus collisions at 400 GeV

We report a new measurement of J/psi, psi' and Drell-Yan cross-sections, in the kinematical domain $-0.425<y_{\rm cm}<0.575$ and $-0.5<\cos\theta_{\rm CS}<0.5$, performed at the CERN-SPS using 400 GeV/c incident protons on Be, Al, Cu, Ag, W and Pb targets. The dependence of the charmonia production cross-sections on the size of the target nucleus allows to quantify the so-called normal nuclear absorption. In the framework of the Glauber model, this new measurement is combined with results previously obtained with the same apparatus, under different experimental conditions, and leads to a precise determination of the J/psi and psi' absorption cross-sections in the surrounding nuclear matter.Comment: Accepted for publication in Euro. Phys. J.

NA50 final results on charmonia suppression

NA50The last results from the NA50 experiment on charmonia production in Pb-Pb interactions at 158 GeV/c per nucleon are presented. A strong J/$\psi$ suppression is observed, which increases with the centrality of the collisions. The J/$\psi$ production is seen to be anomalously suppressed starting at mid-centralities, when compared to a reference taken from proton-induced collisions. The most recent developments on the determination of this normal absorption curve are explained. It is also shown that for sulphur-induced reactions there is full agreement with the extrapolated normal p-A behaviour. The suppression of $\psi'$ production in heavy ion collisions (Pb-Pb and S-U) is also presented. It is seen to increase with the centrality of the collisions, and to be significantly stronger than the one measured in proton-induced reactions

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 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 or ganism 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 ne glected 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 lostinfo:eu-repo/semantics/publishedVersio

Search for heavy gauge W ′ bosons in events with an energetic lepton and large missing transverse momentum at √s = 13 TeV

A search is presented for W′ bosons in events with an electron or muon and large missing transverse momentum, using proton–proton collision data at √s=13 TeV collected with the CMS detector in 2015 and corresponding to an integrated luminosity of 2.3 fb−1. No evidence of an excess of events relative to the standard model expectations is observed. For a W′ boson described by the sequential standard model, upper limits at 95% confidence level are set on the product of the production cross section and branching fraction and lower limits are established on the new boson mass. Masses below 4.1 TeV are excluded combining electron and muon decay channels, significantly improving upon the results obtained with the 8 TeV data. Exclusion limits at 95% confidence level on the product of the W′ production cross section and branching fraction are also derived in combination with the 8 TeV data. Finally, exclusion limits are set for the production of generic W′ bosons decaying into this final state using a model-independent approach

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