1,794 research outputs found
Could petroleum biodegradation be a joint achievement of aerobic and anaerobic microrganisms in deep sea reservoirs?
Several studies suggest that petroleum biodegradation can be achieved by either aerobic or anaerobic microorganisms, depending on oxygen input or other electron acceptors and appropriate nutrients. Evidence from in vitro experiments with samples of petroleum formation water and oils from Pampo Field indicate that petroleum biodegradation is more likely to be a joint achievement of both aerobic and anaerobic bacterial consortium, refining our previous observations of aerobic degradation. The aerobic consortium depleted, in decreasing order, hydrocarbons > hopanes > steranes > tricyclic terpanes while the anaerobic consortium depleted hydrocarbons > steranes > hopanes > tricyclic terpanes. The oxygen content of the mixed consortia was measured from time to time revealing alternating periods of microaerobicity (O2 ~0.8 mg.L-1) and of aerobicity (O2~6.0 mg.L-1). In this experiment, the petroleum biodegradation changed from time to time, alternating periods of biodegradation similar to the aerobic process and periods of biodegradation similar to the anaerobic process. The consortia showed preferences for metabolizing hydrocarbons > hopanes > steranes > tricyclic terpanes during a 90-day period, after which this trend changed and steranes were more biodegraded than hopanes. The analysis of aerobic oil degrading microbiota by the 16S rRNA gene clone library detected the presence of Bacillus, Brevibacterium, Mesorhizobium and Achromobacter, and the analysis of the anaerobic oil degrading microbiota using the same technique detected the presence of Bacillus and Acinetobacter (facultative strains). In the mixed consortia Stenotrophomonas, Brevibacterium, Bacillus, Rhizobium, Achromobacter and 5% uncultured bacteria were detected. This is certainly a new contribution to the study of reservoir biodegradation processes, combining two of the more important accepted hypotheses
Heavy-flavour and quarkonium production in the LHC era: from proton-proton to heavy-ion collisions
This report reviews the study of open heavy-flavour and quarkonium production
in high-energy hadronic collisions, as tools to investigate fundamental aspects
of Quantum Chromodynamics, from the proton and nucleus structure at high energy
to deconfinement and the properties of the Quark-Gluon Plasma. Emphasis is
given to the lessons learnt from LHC Run 1 results, which are reviewed in a
global picture with the results from SPS and RHIC at lower energies, as well as
to the questions to be addressed in the future. The report covers heavy flavour
and quarkonium production in proton-proton, proton-nucleus and nucleus-nucleus
collisions. This includes discussion of the effects of hot and cold strongly
interacting matter, quarkonium photo-production in nucleus-nucleus collisions
and perspectives on the study of heavy flavour and quarkonium with upgrades of
existing experiments and new experiments. The report results from the activity
of the SaporeGravis network of the I3 Hadron Physics programme of the European
Union 7th Framework Programme
Stroke outcome measurements from electronic medical records : cross-sectional study on the effectiveness of neural and nonneural classifiers
Background: With the rapid adoption of electronic medical records (EMRs), there is an ever-increasing opportunity to collect data and extract knowledge from EMRs to support patient-centered stroke management. Objective: This study aims to compare the effectiveness of state-of-the-art automatic text classification methods in classifying data to support the prediction of clinical patient outcomes and the extraction of patient characteristics from EMRs. Methods: Our study addressed the computational problems of information extraction and automatic text classification. We identified essential tasks to be considered in an ischemic stroke value-based program. The 30 selected tasks were classified (manually labeled by specialists) according to the following value agenda: tier 1 (achieved health care status), tier 2 (recovery process), care related (clinical management and risk scores), and baseline characteristics. The analyzed data set was retrospectively extracted from the EMRs of patients with stroke from a private Brazilian hospital between 2018 and 2019. A total of 44,206 sentences from free-text medical records in Portuguese were used to train and develop 10 supervised computational machine learning methods, including state-of-the-art neural and nonneural methods, along with ontological rules. As an experimental protocol, we used a 5-fold cross-validation procedure repeated 6 times, along with subject-wise sampling. A heatmap was used to display comparative result analyses according to the best algorithmic effectiveness (F1 score), supported by statistical significance tests. A feature importance analysis was conducted to provide insights into the results. Results: The top-performing models were support vector machines trained with lexical and semantic textual features, showing the importance of dealing with noise in EMR textual representations. The support vector machine models produced statistically superior results in 71% (17/24) of tasks, with an F1 score >80% regarding care-related tasks (patient treatment location, fall risk, thrombolytic therapy, and pressure ulcer risk), the process of recovery (ability to feed orally or ambulate and communicate), health care status achieved (mortality), and baseline characteristics (diabetes, obesity, dyslipidemia, and smoking status). Neural methods were largely outperformed by more traditional nonneural methods, given the characteristics of the data set. Ontological rules were also effective in tasks such as baseline characteristics (alcoholism, atrial fibrillation, and coronary artery disease) and the Rankin scale. The complementarity in effectiveness among models suggests that a combination of models could enhance the results and cover more tasks in the future. Conclusions: Advances in information technology capacity are essential for scalability and agility in measuring health status outcomes. This study allowed us to measure effectiveness and identify opportunities for automating the classification of outcomes of specific tasks related to clinical conditions of stroke victims, and thus ultimately assess the possibility of proactively using these machine learning techniques in real-world situations
Measurements of meson production in relativistic heavy-ion collisions at RHIC
We present results for the measurement of meson production via its
charged kaon decay channel in Au+Au collisions at
, 130, and 200 GeV, and in and +Au collisions
at GeV from the STAR experiment at the BNL Relativistic
Heavy Ion Collider (RHIC). The midrapidity () meson transverse
momentum () spectra in central Au+Au collisions are found to be well
described by a single exponential distribution. On the other hand, the
spectra from , +Au and peripheral Au+Au collisions show power-law tails
at intermediate and high and are described better by Levy
distributions. The constant yield ratio vs beam species, collision
centrality and colliding energy is in contradiction with expectations from
models having kaon coalescence as the dominant mechanism for production
at RHIC. The yield ratio as a function of is consistent
with a model based on the recombination of thermal quarks up to GeV/, but disagrees at higher transverse momenta. The measured nuclear
modification factor, , for the meson increases above unity at
intermediate , similar to that for pions and protons, while is
suppressed due to the energy loss effect in central Au+Au collisions. Number of
constituent quark scaling of both and for the meson
with respect to other hadrons in Au+Au collisions at =200 GeV
at intermediate is observed. These observations support quark
coalescence as being the dominant mechanism of hadronization in the
intermediate region at RHIC.Comment: 22 pages, 21 figures, 4 table
Growth of Long Range Forward-Backward Multiplicity Correlations with Centrality in Au+Au Collisions at = 200 GeV
Forward-backward multiplicity correlation strengths have been measured with
the STAR detector for Au+Au and collisions at =
200 GeV. Strong short and long range correlations (LRC) are seen in central
Au+Au collisions. The magnitude of these correlations decrease with decreasing
centrality until only short range correlations are observed in peripheral Au+Au
collisions. Both the Dual Parton Model (DPM) and the Color Glass Condensate
(CGC) predict the existence of the long range correlations. In the DPM the
fluctuation in the number of elementary (parton) inelastic collisions produces
the LRC. In the CGC longitudinal color flux tubes generate the LRC. The data is
in qualitative agreement with the predictions from the DPM and indicates the
presence of multiple parton interactions.Comment: 6 pages, 3 figures The abstract has been slightly modifie
Hadronic resonance production in +Au collisions at = 200 GeV at RHIC
We present the first measurements of the , (892),
(1232), (1385), and (1520) resonances in +Au
collisions at = 200 GeV, reconstructed via their hadronic
decay channels using the STAR detector at RHIC. The masses and widths of these
resonances are studied as a function of transverse momentum (). We observe
that the resonance spectra follow a generalized scaling law with the transverse
mass (). The of , , and . The , ,
, , and ratios in
+Au collisions are compared to the measurements in minimum bias
interactions, where we observe that both measurements are comparable. The
nuclear modification factors () of the , , and
scale with the number of binary collisions () for 1.2 GeV/.Comment: STAR Collaboration. Submitted to PR
Studying Parton Energy Loss in Heavy-Ion Collisions via Direct-Photon and Charged-Particle Azimuthal Correlations
Charged-particle spectra associated with direct photon () and
are measured in + and Au+Au collisions at center-of-mass energy
GeV with the STAR detector at RHIC. A hower-shape
analysis is used to partially discriminate between and .
Assuming no associated charged particles in the direction (near
side) and small contribution from fragmentation photons (), the
associated charged-particle yields opposite to (away side) are
extracted. At mid-rapidity () in central Au+Au collisions,
charged-particle yields associated with and at high
transverse momentum ( GeV/) are suppressed by a factor
of 3-5 compared with + collisions. The observed suppression of the
associated charged particles, in the kinematic range and GeV/, is similar for and , and
independent of the energy within uncertainties. These
measurements indicate that the parton energy loss, in the covered kinematic
range, is insensitive to the parton path length.Comment: submitted to Phys. Rev. Lett, 6 pages, 4 figure
Systematic Measurements of Identified Particle Spectra in pp, d+Au and Au+Au Collisions from STAR
Identified charged particle spectra of , , and
\pbar at mid-rapidity () measured by the \dedx method in the
STAR-TPC are reported for and d+Au collisions at \snn = 200 GeV and for
Au+Au collisions at 62.4 GeV, 130 GeV, and 200 GeV. ... [Shortened for arXiv
list. Full abstract in manuscript.]Comment: 58 pages, 46 figures, 37 table
K/pi Fluctuations at Relativistic Energies
We report results for fluctuations from Au+Au collisions at
= 19.6, 62.4, 130, and 200 GeV using the STAR detector at the
Relativistic Heavy Ion Collider. Our results for fluctuations in
central collisions show little dependence on the incident energies studied and
are on the same order as results observed by NA49 at the Super Proton
Synchrotron in central Pb+Pb collisions at = 12.3 and 17.3 GeV.
We also report results for the collision centrality dependence of
fluctuations as well as results for , ,
, and fluctuations. We observe that the
fluctuations scale with the multiplicity density, , rather than the
number of participating nucleons.Comment: 6 pages, 4 figure
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