Investigation of slug mitigation: self-lifting approach in a deepwater oil field

Slug flow is a flow assurance issue that staggers production and, in some cases, 'kills the flow' of the well. Severe slugging, a type of slugging which usually occurs at the base of the riser column, causes large amplitudes in the fluctuation of pressure within the riser column and consequently damages equipment placed topside. An adaptation of a novel concept to slug mitigation: the self-lifting model, is presented. This model presents variations to the internal diameter of the self-lift bypass to produce effective mitigation to severe slugging

Compensation of B-L charge of matter with relic sneutrinos

We consider massless gauge boson connected to B-L charge with and without compensation to complete the investigation of the gauging of B and L charges. Relic sneutrinos predicted by SUSY and composite models may compensate B-L charge of matter. As a consequence of the possible compensation mechanism we have shown that the available experimental data admit the range of the B-L interaction constant, 10^{-29} < {\alpha}_{B-L} < 10^{-12}, in addition to {\alpha}_{B-L} < 10^{-49} obtained without compensation.Comment: 6 page

Doppler effect on nanopatterning with nonlinear laser lithography

[No abstract available

Possibilities of transcranial direct current stimulation (tDCS) use in elite sport

Transcranial direct current stimulation has proven to be the method that can modulate neural activity in various cases. As this method has been shown to be effective in improving muscular strength, reaction time and accuracy, motor learning, it seems to be promising in elite sports.This paper provides an overview of studies on tDCS and its impact on central nervous system functioning, with an emphasis on potential sports utility. This review demonstrates that the basic mechanism of the effect of tDCS on nervous system functioning is its ability to modulate the excitability of neurons.tDCS is able to influence various components of electrocortical potentials, the amplitude of the motor evoked potential, as well as the mechanisms of long-term potentiation and, as a consequence, the cellular mechanisms of motor learning and neuroplasticity in general. The beneficial effect of tDCS on attention selectivity and signal detection has been noted. It is also shown that tDCS can accelerate learning and enhance performance in a range of complex cognitive tasks.In addition, a number of studies showing that tDCS can increase the efficiency of performing arithmetic and problem solving tasks are considered.In the context of sports, the influence of tDCS over motor areas on motor learning and on the accuracy of voluntary movements seems to be important. Its ability to influence speed and strength indicators, namely, the maximum isometric force of various muscle groups and explosive strength, as well as endurance indicators seems promising, too. The review also shows that tDCS is reasonably safe and that serious adverse effects are extremely rare; the most common adverse effect is local skin irritation due to poor electrode placement

Active learning with RESSPECT: Resource allocation for extragalactic astronomical transients

The authors would like to thank David Kirkby and Connor Sheere for insightful discussions. This work is part of the Recommendation System for Spectroscopic Followup (RESSPECT) project, governed by an inter-collaboration agreement signed between the Cosmostatistics Initiative (COIN) and the LSST Dark Energy Science Collaboration (DESC). This research is supported in part by the HPI Research Center in Machine Learning and Data Science at UC Irvine. EEOI and SS acknowledge financial support from CNRS 2017 MOMENTUM grant under the project Active Learning for Large Scale Sky Surveys. SGG and AKM acknowledge support by FCT under Project CRISP PTDC/FIS-AST-31546/2017. This work was partly supported by the Hewlett Packard Enterprise Data Science Institute (HPE DSI) at the University of Houston. DOJ is supported by a Gordon and Betty Moore Foundation postdoctoral fellowship at the University of California, Santa Cruz. Support for this work was provided by NASA through the NASA Hubble Fellowship grant HF2-51462.001 awarded by the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Inc., for NASA, under contract NAS5-26555. BQ is supported by the International Gemini Observatory, a program of NSF's NOIRLab, which is managed by the Association of Universities for Research in Astronomy (AURA) under a cooperative agreement with the National Science Foundation, on behalf of the Gemini partnership of Argentina, Brazil, Canada, Chile, the Republic of Korea, and the United States of America. AIM acknowledges support from the Max Planck Society and the Alexander von Humboldt Foundation in the framework of the Max Planck-Humboldt Research Award endowed by the Federal Ministry of Education and Research. L.G. was funded by the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 839090. This work has been partially supported by the Spanish grant PGC2018-095317-B-C21 within the European Funds for Regional Development (FEDER).The recent increase in volume and complexity of available astronomical data has led to a wide use of supervised machine learning techniques. Active learning strategies have been proposed as an alternative to optimize the distribution of scarce labeling resources. However, due to the specific conditions in which labels can be acquired, fundamental assumptions, such as sample representativeness and labeling cost stability cannot be fulfilled. The Recommendation System for Spectroscopic followup (RESSPECT) project aims to enable the construction of optimized training samples for the Rubin Observatory Legacy Survey of Space and Time (LSST), taking into account a realistic description of the astronomical data environment. In this work, we test the robustness of active learning techniques in a realistic simulated astronomical data scenario. Our experiment takes into account the evolution of training and pool samples, different costs per object, and two different sources of budget. Results show that traditional active learning strategies significantly outperform random sampling. Nevertheless, more complex batch strategies are not able to significantly overcome simple uncertainty sampling techniques. Our findings illustrate three important points: 1) active learning strategies are a powerful tool to optimize the label-acquisition task in astronomy, 2) for upcoming large surveys like LSST, such techniques allow us to tailor the construction of the training sample for the first day of the survey, and 3) the peculiar data environment related to the detection of astronomical transients is a fertile ground that calls for the development of tailored machine learning algorithms.HPI Research Center in Machine Learning and Data Science at UC IrvineCNRS 2017 MOMENTUM grant under the project Active Learning for Large Scale Sky SurveysFCT under Project CRISP PTDC/FIS-AST-31546/2017Hewlett Packard Enterprise Data Science Institute (HPE DSI) at the University of HoustonGordon and Betty Moore Foundation postdoctoral fellowship at the University of California, Santa CruzSpace Telescope Science InstituteNational Aeronautics & Space Administration (NASA) HF2-51462.001 NAS5-26555International Gemini Observatory, a program of NSF's NOIRLabNational Science Foundation (NSF)Max Planck SocietyFoundation CELLEXAlexander von Humboldt FoundationEuropean Commission 839090Spanish grant within the European Funds for Regional Development (FEDER) PGC2018-095317-B-C2

De Novo Transcriptome Assembly and Comparative Analysis Elucidate Complicated Mechanism Regulating Astragalus chrysochlorus Response to Selenium Stimuli

Astragalus species are medicinal plants that are used in the world for years. Some Astragalus species are known for selenium accumulation and tolerance and one of them is Astragalus chrysochlorus, a secondary selenium accumulator. In this study, we employed Illumina deep sequencing technology for the first time to de novo assemble A. chrysochlorus transcriptome and identify the differentially expressed genes after selenate treatment. Totally, 59,656 unigenes were annotated with different databases and 53,960 unigenes were detected in NR database. Transcriptome in A. chrysochlorus is closer to Glycine max than other plant species with 43,1 percentage of similarity. Annotated unigenes were also used for gene ontology enrichment and pathway enrichment analysis. The most significant genes and pathways were ABC transporters, plant pathogen interaction, biosynthesis of secondary metabolites and carbohydrate metabolism. Our results will help to enlighten the selenium accumulation and tolerance mechanisms, respectively in plants

Search for the Standard Model Higgs Boson with the OPAL Detector at LEP

This paper summarises the search for the Standard Model Higgs boson in e+e- collisions at centre-of-mass energies up to 209 GeV performed by the OPAL Collaboration at LEP. The consistency of the data with the background hypothesis and various Higgs boson mass hypotheses is examined. No indication of a signal is found in the data and a lower bound of 112.7GeV/C^2 is obtained on the mass of the Standard Model Higgs boson at the 95% CL.Comment: 51 pages, 21 figure

Measurement of the Hadronic Photon Structure Function F_2^gamma at LEP2

The hadronic structure function of the photon F_2^gamma is measured as a function of Bjorken x and of the factorisation scale Q^2 using data taken by the OPAL detector at LEP. Previous OPAL measurements of the x dependence of F_2^gamma are extended to an average Q^2 of 767 GeV^2. The Q^2 evolution of F_2^gamma is studied for average Q^2 between 11.9 and 1051 GeV^2. As predicted by QCD, the data show positive scaling violations in F_2^gamma. Several parameterisations of F_2^gamma are in agreement with the measurements whereas the quark-parton model prediction fails to describe the data.Comment: 4 pages, 2 figures, to appear in the proceedings of Photon 2001, Ascona, Switzerlan

Search for R-Parity Violating Decays of Scalar Fermions at LEP

A search for pair-produced scalar fermions under the assumption that R-parity is not conserved has been performed using data collected with the OPAL detector at LEP. The data samples analysed correspond to an integrated luminosity of about 610 pb-1 collected at centre-of-mass energies of sqrt(s) 189-209 GeV. An important consequence of R-parity violation is that the lightest supersymmetric particle is expected to be unstable. Searches of R-parity violating decays of charged sleptons, sneutrinos and squarks have been performed under the assumptions that the lightest supersymmetric particle decays promptly and that only one of the R-parity violating couplings is dominant for each of the decay modes considered. Such processes would yield final states consisting of leptons, jets, or both with or without missing energy. No significant single-like excess of events has been observed with respect to the Standard Model expectations. Limits on the production cross- section of scalar fermions in R-parity violating scenarios are obtained. Constraints on the supersymmetric particle masses are also presented in an R-parity violating framework analogous to the Constrained Minimal Supersymmetric Standard Model.Comment: 51 pages, 24 figures, Submitted to Eur. Phys. J.