421 research outputs found

    Structure factor of polymers interacting via a short range repulsive potential: application to hairy wormlike micelles

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    We use the Random Phase Approximation (RPA) to compute the structure factor, S(q), of a solution of chains interacting through a soft and short range repulsive potential V. Above a threshold polymer concentration, whose magnitude is essentially controlled by the range of the potential, S(q) exhibits a peak whose position depends on the concentration. We take advantage of the close analogy between polymers and wormlike micelles and apply our model, using a Gaussian function for V, to quantitatively analyze experimental small angle neutron scattering profiles of semi-dilute solutions of hairy wormlike micelles. These samples, which consist in surfactant self-assembled flexible cylinders decorated by amphiphilic copolymer, provide indeed an appropriate experimental model system to study the structure of sterically interacting polymer solutions

    The use of chest ultrasonography in suspected cases of COVID-19 in the emergency department

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    Aim: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus-specific reverse transcriptase-polymerase chain reaction (RT-PCR) represents the diagnostic gold standard. We explored the value of chest ultrasonography to predict positivity to SARS-CoV-2 on RT-PCR in suspected COVID-19 cases. Patients & methods: Consecutive patients with suspect COVID-19 were included if they had fever and/or history of cough and/or dyspnea. Lung ultrasound score (LUSS) was computed according to published methods. Results: A total of 76 patients were included. A 3-variable model based on aspartate transaminase (AST) > upper limit of normal, LUSS >12 and body temperature >37.5°C yielded an overall accuracy of 91%. Conclusion: A simple LUSS-based model may represent a powerful tool for initial assessment in suspected cases of COVID-19. The gold standard for diagnosis of COVID-19 is RT-PCR. During a pandemic emergency, it may be useful to identify suspect symptomatic patients who may safely be observed without undergoing testing for COVID-19. In this work, a simple model based on the findings of lung ultrasound, AST levels and fever showed an overall accuracy of 91% to predict the results of RT-PCR

    Multi-Particle Collision Dynamics -- a Particle-Based Mesoscale Simulation Approach to the Hydrodynamics of Complex Fluids

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    In this review, we describe and analyze a mesoscale simulation method for fluid flow, which was introduced by Malevanets and Kapral in 1999, and is now called multi-particle collision dynamics (MPC) or stochastic rotation dynamics (SRD). The method consists of alternating streaming and collision steps in an ensemble of point particles. The multi-particle collisions are performed by grouping particles in collision cells, and mass, momentum, and energy are locally conserved. This simulation technique captures both full hydrodynamic interactions and thermal fluctuations. The first part of the review begins with a description of several widely used MPC algorithms and then discusses important features of the original SRD algorithm and frequently used variations. Two complementary approaches for deriving the hydrodynamic equations and evaluating the transport coefficients are reviewed. It is then shown how MPC algorithms can be generalized to model non-ideal fluids, and binary mixtures with a consolute point. The importance of angular-momentum conservation for systems like phase-separated liquids with different viscosities is discussed. The second part of the review describes a number of recent applications of MPC algorithms to study colloid and polymer dynamics, the behavior of vesicles and cells in hydrodynamic flows, and the dynamics of viscoelastic fluids

    Advanced Virgo Plus: Future Perspectives

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    While completing the commissioning phase to prepare the Virgo interferometer for the next joint Observation Run (O4), the Virgo collaboration is also finalizing the design of the next upgrades to the detector to be employed in the following Observation Run (O5). The major upgrade will concern decreasing the thermal noise limit, which will imply using very large test masses and increased laser beam size. But this will not be the only upgrade to be implemented in the break between the O4 and O5 observation runs to increase the Virgo detector strain sensitivity. The paper will cover the challenges linked to this upgrade and implications on the detector's reach and observational potential, reflecting the talk given at 12th Cosmic Ray International Seminar - CRIS 2022 held in September 2022 in Napoli

    The Advanced Virgo+ status

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    The gravitational wave detector Advanced Virgo+ is currently in the commissioning phase in view of the fourth Observing Run (O4). The major upgrades with respect to the Advanced Virgo configuration are the implementation of an additional recycling cavity, the Signal Recycling cavity (SRC), at the output of the interferometer to broaden the sensitivity band and the Frequency Dependent Squeezing (FDS) to reduce quantum noise at all frequencies. The main difference of the Advanced Virgo + detector with respect to the LIGO detectors is the presence of marginally stable recycling cavities, with respect to the stable recycling cavities present in the LIGO detectors, which increases the difficulties in controlling the interferometer in presence of defects (both thermal and cold defects). This work will focus on the interferometer commissioning, highlighting the control challenges to maintain the detector in the working point which maximizes the sensitivity and the duty cycle for scientific data taking

    Virgo Detector Characterization and Data Quality during the O3 run

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    The Advanced Virgo detector has contributed with its data to the rapid growth of the number of detected gravitational-wave signals in the past few years, alongside the two LIGO instruments. First, during the last month of the Observation Run 2 (O2) in August 2017 (with, most notably, the compact binary mergers GW170814 and GW170817) and then during the full Observation Run 3 (O3): an 11 months data taking period, between April 2019 and March 2020, that led to the addition of about 80 events to the catalog of transient gravitational-wave sources maintained by LIGO, Virgo and KAGRA. These discoveries and the manifold exploitation of the detected waveforms require an accurate characterization of the quality of the data, such as continuous study and monitoring of the detector noise. These activities, collectively named {\em detector characterization} or {\em DetChar}, span the whole workflow of the Virgo data, from the instrument front-end to the final analysis. They are described in details in the following article, with a focus on the associated tools, the results achieved by the Virgo DetChar group during the O3 run and the main prospects for future data-taking periods with an improved detector.Comment: 86 pages, 33 figures. This paper has been divided into two articles which supercede it and have been posted to arXiv on October 2022. Please use these new preprints as references: arXiv:2210.15634 (tools and methods) and arXiv:2210.15633 (results from the O3 run

    Virgo Detector Characterization and Data Quality: results from the O3 run

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    The Advanced Virgo detector has contributed with its data to the rapid growth of the number of detected gravitational-wave (GW) signals in the past few years, alongside the two Advanced LIGO instruments. First during the last month of the Observation Run 2 (O2) in August 2017 (with, most notably, the compact binary mergers GW170814 and GW170817), and then during the full Observation Run 3 (O3): an 11-months data taking period, between April 2019 and March 2020, that led to the addition of about 80 events to the catalog of transient GW sources maintained by LIGO, Virgo and now KAGRA. These discoveries and the manifold exploitation of the detected waveforms require an accurate characterization of the quality of the data, such as continuous study and monitoring of the detector noise sources. These activities, collectively named {\em detector characterization and data quality} or {\em DetChar}, span the whole workflow of the Virgo data, from the instrument front-end hardware to the final analyses. They are described in details in the following article, with a focus on the results achieved by the Virgo DetChar group during the O3 run. Concurrently, a companion article describes the tools that have been used by the Virgo DetChar group to perform this work.Comment: 57 pages, 18 figures. To be submitted to Class. and Quantum Grav. This is the "Results" part of preprint arXiv:2205.01555 [gr-qc] which has been split into two companion articles: one about the tools and methods, the other about the analyses of the O3 Virgo dat

    Virgo Detector Characterization and Data Quality: tools

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    Detector characterization and data quality studies -- collectively referred to as {\em DetChar} activities in this article -- are paramount to the scientific exploitation of the joint dataset collected by the LIGO-Virgo-KAGRA global network of ground-based gravitational-wave (GW) detectors. They take place during each phase of the operation of the instruments (upgrade, tuning and optimization, data taking), are required at all steps of the dataflow (from data acquisition to the final list of GW events) and operate at various latencies (from near real-time to vet the public alerts to offline analyses). This work requires a wide set of tools which have been developed over the years to fulfill the requirements of the various DetChar studies: data access and bookkeeping; global monitoring of the instruments and of the different steps of the data processing; studies of the global properties of the noise at the detector outputs; identification and follow-up of noise peculiar features (whether they be transient or continuously present in the data); quick processing of the public alerts. The present article reviews all the tools used by the Virgo DetChar group during the third LIGO-Virgo Observation Run (O3, from April 2019 to March 2020), mainly to analyse the Virgo data acquired at EGO. Concurrently, a companion article focuses on the results achieved by the DetChar group during the O3 run using these tools.Comment: 44 pages, 16 figures. To be submitted to Class. and Quantum Grav. This is the "Tools" part of preprint arXiv:2205.01555 [gr-qc] which has been split into two companion articles: one about the tools and methods, the other about the analyses of the O3 Virgo dat
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