Fractional Distillation of Bio-Oil Produced by Pyrolysis of Açaí (Euterpe oleracea) Seeds

In this work, the seeds of açaí (Euterpe oleracea, Mart), a rich lignin-cellulose residue, has been submitted to pyrolysis to produce a bio-oil-like fossil fuels. The pyrolysis carried out in a reactor of 143 L, 450°C, and 1.0 atm. The morphology of Açaí seeds in nature and after pyrolysis is characterized by SEM, EDX, and XRD. The experiments show that bio-oil, gas, and coke yields were 4.38, 30.56, and 35.67% (wt.), respectively. The bio-oil characterized by AOCS, ASTM, and ABNT/NBR methods for density, kinematic viscosity, and acid value. The bio-oil density, viscosity, and acid value were 1.0468 g/cm3, 68.34 mm2/s, and 70.26 KOH/g, respectively. The chemical composition and chemical functions of bio-oil are determined by GC-MS and FT-IR. The GC-MS identified in bio-oil 21.52% (wt.) hydrocarbons and 78.48% (wt.) oxygenates (4.06% esters, 8.52% carboxylic acids, 3.53% ketones, 35.16% phenols, 20.52% cresols, 5.75% furans, and 0.91% (wt.) aldehydes), making it possible to apply fractional distillation to obtain fossil fuel-like fractions rich in hydrocarbons. The distillation of bio-oil is carried out in a laboratory-scale column, according to the boiling temperature of fossil fuels. The distillation of bio-oil yielded fossil fuel-like fractions (gasoline, kerosene, and light diesel) of 4.70, 28.21, and 22.35% (wt.), respectively

Análise da composição química do Bio-Óleo produzido via pirólise de sementes de Açaí (Euterpe Oleracea, Mart) / Chemical analysis of Bio-Oil produced by pyrolise of Açaí (Euterpe Oleracea, Mart) seeds

Neste trabalho, a influência da temperatura na composição química (hidrocarbonetos e produtos oxigenados) do bio-óleo obtido via pirólise de sementes do Açaí (Euterpe oleracea, Mart.), um resíduo rico em lignina-celulose, foi sistematicamente investigada em escala piloto. A reação de pirólise foi realizada em reator de 143 L, operando em modo batelada a 350, 400 e 450 ºC, 1,0 atmosfera. A composição química e a análise qualitativa das funções e/ou grupos presentes no bio-óleo foram determinadas por GC-MS e FT-IR. A análise de FT-IR identificou funções químicas características de hidrocarbonetos (alcanos, alcenos e aromáticos) e oxigenados (fenóis, cresóis, cetonas, ésteres, ácidos carboxílicos, aldeídos e furanos) no bio-óleo. A análise de GC-MS identificou hidrocarbonetos e oxigenados como principais compostos químicos do bio-óleo, com composição química fortemente dependentes da temperatura de pirólise. A concentração de hidrocarbonetos no bio-óleo variou entre 13,505 e 21,542% (área.), aumentando com a temperatura, enquanto a dos produtos oxigenados variaram entre 78,458 e 86,495% (área.), diminui com a temperatura de pirólise. A composição de alcanos, alcenos e aromáticos aumenta com a temperatura, mostrando que temperaturas mais altas favorecem a formação de hidrocarbonetos

Standalone vertex finding in the ATLAS muon spectrometer

A dedicated reconstruction algorithm to find decay vertices in the ATLAS muon spectrometer is presented. The algorithm searches the region just upstream of or inside the muon spectrometer volume for multi-particle vertices that originate from the decay of particles with long decay paths. The performance of the algorithm is evaluated using both a sample of simulated Higgs boson events, in which the Higgs boson decays to long-lived neutral particles that in turn decay to bbar b final states, and pp collision data at √s = 7 TeV collected with the ATLAS detector at the LHC during 2011

Measurements of Higgs boson production and couplings in diboson final states with the ATLAS detector at the LHC

Measurements are presented of production properties and couplings of the recently discovered Higgs boson using the decays into boson pairs, H →γ γ, H → Z Z∗ →4l and H →W W∗ →lνlν. The results are based on the complete pp collision data sample recorded by the ATLAS experiment at the CERN Large Hadron Collider at centre-of-mass energies of √s = 7 TeV and √s = 8 TeV, corresponding to an integrated luminosity of about 25 fb−1. Evidence for Higgs boson production through vector-boson fusion is reported. Results of combined fits probing Higgs boson couplings to fermions and bosons, as well as anomalous contributions to loop-induced production and decay modes, are presented. All measurements are consistent with expectations for the Standard Model Higgs boson

The Fourteenth Data Release of the Sloan Digital Sky Survey: First Spectroscopic Data from the extended Baryon Oscillation Spectroscopic Survey and from the second phase of the Apache Point Observatory Galactic Evolution Experiment

The fourth generation of the Sloan Digital Sky Survey (SDSS-IV) has been in operation since July 2014. This paper describes the second data release from this phase, and the fourteenth from SDSS overall (making this, Data Release Fourteen or DR14). This release makes public data taken by SDSS-IV in its first two years of operation (July 2014-2016). Like all previous SDSS releases, DR14 is cumulative, including the most recent reductions and calibrations of all data taken by SDSS since the first phase began operations in 2000. New in DR14 is the first public release of data from the extended Baryon Oscillation Spectroscopic Survey (eBOSS); the first data from the second phase of the Apache Point Observatory (APO) Galactic Evolution Experiment (APOGEE-2), including stellar parameter estimates from an innovative data driven machine learning algorithm known as "The Cannon"; and almost twice as many data cubes from the Mapping Nearby Galaxies at APO (MaNGA) survey as were in the previous release (N = 2812 in total). This paper describes the location and format of the publicly available data from SDSS-IV surveys. We provide references to the important technical papers describing how these data have been taken (both targeting and observation details) and processed for scientific use. The SDSS website (www.sdss.org) has been updated for this release, and provides links to data downloads, as well as tutorials and examples of data use. SDSS-IV is planning to continue to collect astronomical data until 2020, and will be followed by SDSS-V.Comment: SDSS-IV collaboration alphabetical author data release paper. DR14 happened on 31st July 2017. 19 pages, 5 figures. Accepted by ApJS on 28th Nov 2017 (this is the "post-print" and "post-proofs" version; minor corrections only from v1, and most of errors found in proofs corrected

Measurement of the top quark pair cross section with ATLAS in pp collisions at √s=7 TeV using final states with an electron or a muon and a hadronically decaying τ lepton

A measurement of the cross section of top quark pair production in proton-proton collisions recorded with the ATLAS detector at the Large Hadron Collider at a centre-of-mass energy of 7 TeV is reported. The data sample used corresponds to an integrated luminosity of 2.05 fb -1. Events with an isolated electron or muon and a τ lepton decaying hadronically are used. In addition, a large missing transverse momentum and two or more energetic jets are required. At least one of the jets must be identified as originating from a b quark. The measured cross section, σtt-=186±13(stat.)±20(syst.)±7(lumi.) pb, is in good agreement with the Standard Model prediction

Hunt for new phenomena using large jet multiplicities and missing transverse momentum with ATLAS in 4.7 fb−1 of √s=7 TeV proton-proton collisions

Results are presented of a search for new particles decaying to large numbers of jets in association with missing transverse momentum, using 4.7 fb−1 of pp collision data at s√=7TeV collected by the ATLAS experiment at the Large Hadron Collider in 2011. The event selection requires missing transverse momentum, no isolated electrons or muons, and from ≥6 to ≥9 jets. No evidence is found for physics beyond the Standard Model. The results are interpreted in the context of a MSUGRA/CMSSM supersymmetric model, where, for large universal scalar mass m 0, gluino masses smaller than 840 GeV are excluded at the 95% confidence level, extending previously published limits. Within a simplified model containing only a gluino octet and a neutralino, gluino masses smaller than 870 GeV are similarly excluded for neutralino masses below 100 GeV

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