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The first twenty years of operation of gravitational-wave interferometers have shown that these detectors are affected by physical disturbances from the surrounding environment. These are seismic, acoustic, or electromagnetic disturbances that are mainly produced by the experiment infrastructure itself. Ambient noise can limit the interferometer sensitivity or potentially generate transients of non-astrophysical origin. Between 1 April 2019 and 27 March 2020, the network of second generation interferometers—LIGO, Virgo and GEO—performed the third joined observing run, named O3, searching for gravitational signals from the deep universe. A thorough investigation has been done on each detector before and during data taking in order to optimize its sensitivity and duty cycle. In this paper, we first revisit typical sources of environmental noise and their coupling paths, and we then describe investigation methods and tools. Finally, we illustrate applications of these methods in the hunt for environmental noise at the Virgo interferometer during the O3 run and its preparation phase. In particular, we highlight investigation techniques that might be useful for the next observing runs and the future generation of terrestrial interferometers.

Background and Objectives: In patients with COVID-19, high-flow nasal cannula (HFNC) and continuous positive airway pressure (CPAP) are widely applied as initial treatments for moderate-to-severe acute hypoxemic respiratory failure. The aim of the study was to assess which respiratory supports improve 28-day mortality and to identify a predictive index of treatment response. Materials and Methods: This is a single-center retrospective observational study including 159 consecutive adult patients with COVID-19 and moderate-to-severe hypoxemic acute respiratory failure. Results: A total of 159 patients (82 in the CPAP group and 77 in the HFNC group) were included in the study. Mortality within 28 days was significantly lower with HFNC compared to CPAP (16.8% vs. 50%), while ICU admission and tracheal intubation within 28 days were significantly higher with CPAP compared to HFNC treatment (32% vs. 13%). We identified an index for survival in HFNC by including three variables easily available at admission (LDH, age, and respiratory rate) and the PaO2/FiO2 ratio at 48 h. The index showed high discrimination for survival with an AUC of 0.88, a negative predictive value of 86%, and a positive predictive value of 95%. Conclusions: Treatment with HFNC appears to be associated with greater survival and fewer ICU admission than CPAP. LDH, respiratory rate, age, and PaO2/FiO2 at 48 h were independently associated with survival and an index based on these variables allows for the prediction of treatment success and the assessment of patient allocation to the appropriate intensity of care after 48 h. Further research is warranted to determine effects on other outcomes and to assess the performance of the index in larger cohorts.

Background: During the SARS-CoV-2 pandemic, several biomarkers were shown to be helpful in determining the prognosis of COVID-19 patients. The aim of our study was to evaluate the prognostic value of N-terminal pro-Brain Natriuretic Peptide (NT-pro-BNP) in a cohort of patients with COVID-19. Methods: One-hundred and seven patients admitted to the Covid Hospital of Messina University between June 2022 and January 2023 were enrolled in our study. The demographic, clinical, biochemical, instrumental, and therapeutic parameters were recorded. The primary outcome was in-hospital mortality. A comparison between patients who recovered and were discharged and those who died during the hospitalization was performed. The independent parameters associated with in-hospital death were assessed by multivariable analysis and a stepwise regression logistic model. Results: A total of 27 events with an in-hospital mortality rate of 25.2% occurred during our study. Those who died during hospitalization were older, with lower GCS and PaO2/FiO2 ratio, elevated D-dimer values, INR, creatinine values and shorter PT (prothrombin time). They had an increased frequency of diagnosis of heart failure (p < 0.0001) and higher NT-pro-BNP values. A multivariate logistic regression analysis showed that higher NT-pro-BNP values and lower PT and PaO2/FiO2 at admission were independent predictors of mortality during hospitalization. Conclusions: This study shows that NT-pro-BNP levels, PT, and PaO2/FiO2 ratio are independently associated with in-hospital mortality in subjects with COVID-19 pneumonia. Further longitudinal studies are warranted to confirm the results of this study.

Objective: Coronavirus disease 2019 (COVID-19) is a disease with a high rate of progression to critical illness. However, the stratification of patients at risk of mortality is not well defined. In this study, we aimed to define a mortality risk index to allocate patients to the appropriate intensity of care. Methods: This is a 12 months observational longitudinal study designed to develop and validate a pragmatic mortality risk score to stratify COVID-19 patients aged ≥18 years and admitted to hospital between March 2020 and March 2021. Main outcome was in-hospital mortality. Results: 244 patients were included in the study (mortality rate 29.9%). The Covid-19 Assessment for Survival at Admission (CASA) index included seven variables readily available at admission: respiratory rate, troponin, albumin, CKD-EPI, white blood cell count, D-dimer, Pa02/Fi02. The CASA index showed high discrimination for mortality with an AUC of 0.91 (sensitivity 98.6%; specificity 69%) and a better performance compared to SOFA (AUC = 0.76), age (AUC = 0.76) and 4C mortality (AUC = 0.82). The cut-off identified (11.994) for CASA index showed a negative predictive value of 99.16% and a positive predictive value of 57.58%. Conclusions: A quick and readily available index has been identified to help clinicians stratify COVID-19 patients according to the appropriate intensity of care and minimize hospital admission to patients at high risk of mortality.

Systemic sclerosis (SSc) is a complex rare autoimmune disease with heterogeneous clinical manifestations. Currently, interstitial lung disease (ILD) and cardiac involvement (including pulmonary arterial hypertension) are recognized as the leading causes of SSc-associated mortality. New molecular targets have been discovered and phase II and phase III clinical trials published in the last 5 years on SSc-ILD will be discussed in this review. Details on the study design; the drug tested and its dose; the inclusion and exclusion criteria of the study; the concomitant immunosuppression; the outcomes and the duration of the study were reviewed. The two most common drugs used for the treatment of SSc-ILD are cyclophosphamide and mycophenolate mofetil, both supported by randomized controlled trials. Additional drugs, such as nintedanib and tocilizumab, have been approved to slow pulmonary function decline in SSc-ILD. In this review, we discuss the therapeutic alternatives for SSc management, offering the option to customize the design of future studies to stratify SSc patients and provide a patient-specific treatment according to the new emerging pathogenic features of SSc-ILD.

Terrestrial gravity perturbations caused by seismic fields produce the so-called Newtonian noise in gravitational-wave detectors, which is predicted to limit their sensitivity in the upcoming observing runs. In the past, this noise was seen as an infrastructural limitation, i.e., something that cannot be overcome without major investments to improve a detector’s infrastructure. However, it is possible to have at least an indirect estimate of this noise by using the data from a large number of seismometers deployed around a detector’s suspended test masses. The noise estimate can be subtracted from the gravitational-wave data, a process called Newtonian noise cancellation (NNC). In this article, we present the design and implementation of the first NNC system at the Virgo detector as part of its AdV+ upgrade. It uses data from 110 vertical geophones deployed inside the Virgo buildings in optimized array configurations. We use a separate tiltmeter channel to test the pipeline in a proof-of-principle. The system has been running with good performance over months.

The area surrounding the dismissed mine of Sos Enattos (Sardinia, Italy) is the Italian candidate site for hosting Einstein Telescope (ET), the third-generation gravitational wave (GW) observatory. One of the goals of ET is to extend the sensitivity down to frequencies well below those currently achieved by GW detectors, i.e. down to 2 Hz. In the bandwidth [1,10] Hz, the seismic noise of anthropogenic origin is expected to represent the major perturbation to the operation of the infrastructure, and the site that will host the future detector must fulfill stringent requirements on seismic disturbances. In this paper we describe the operation of a temporary, 15-element, seismic array deployed in close proximity to the mine. Signals of anthropogenic origin have a transient nature, and their spectra are characterized by a wide spectral lobe spanning the [3,20] Hz frequency interval. Superimposed to this wide lobe are narrow spectral peaks within the [3,8] Hz frequency range. Results from slowness analyses suggest that the origin of these peaks is related to vehicle traffic along the main road running east of the mine. Exploiting the correlation properties of seismic noise, we derive a dispersion curve for Rayleigh waves, which is then inverted for a shallow velocity structure down to depths of ≈ 150 m. This data, which is consistent with that derived from analysis of a quarry blast, provide a first assessment of the elastic properties of the rock materials at the site candidate to hosting ET.

Fluctuations of gravitational forces cause so-called Newtonian noise (NN) in gravitational-wave (GW) detectors which is expected to limit their low-frequency sensitivity in upcoming observing runs. Seismic NN is produced by seismic waves passing near a detector's suspended test masses. It is predicted to be the strongest contribution to NN. Modeling this contribution accurately is a major challenge. Arrays of seismometers were deployed at the Virgo site to characterize the seismic field near the four test masses. In this paper, we present results of a spectral analysis of the array data from one of Virgo's end buildings to identify dominant modes of the seismic field. Some of the modes can be associated with known seismic sources. Analyzing the modes over a range of frequencies, we provide a dispersion curve of Rayleigh waves. We find that the Rayleigh speed in the NN frequency band 10 Hz - 20 Hz is very low (\\(\\lesssim\\)100\\,m/s), which has important consequences for Virgo's seismic NN. Using the new speed estimate, we find that the recess formed under the suspended test masses by a basement level at the end buildings leads to a 10 fold reduction of seismic NN.

Gravitational waves emitted during the coalescence of binary neutron star systems carry information about the equation of state describing the extremely dense matter inside neutron stars. In particular, the equation of state determines the fate of the binary after the merger: a prompt collapse to black hole, or the formation of a neutron star remnant that is either stable or survives up to a few seconds before collapsing to a black hole. Determining the evolution of a binary neutron star system will therefore place strong constraints on the equation of state. We present a morphology-independent method, developed in the framework of the coherentWaveBurst analysis of signals from ground-based interferometric detectors of gravitational waves. The method characterizes the time-frequency postmerger gravitational-wave emission from a binary neutron star system, and determines whether, after the merger, it formed a remnant neutron star or promptly collapsed to a black hole. We measure the following quantities to characterize the postmerger emission: ratio of signal energies and match of luminosity profile in different frequency bands, weighted central frequency and bandwidth. From these quantities, based on the study of signals simulated through injections of numerical relativity waveforms, we build a statistics to discriminate between the different scenarios after the merger. Finally, we test our method on a set of signals simulated with new models, to estimate its efficiency as a function of the source distance.

A system was recently implemented in the Virgo detector to cancel noise in its data produced by seismic waves directly coupling with the suspended test masses through gravitational interaction. The data from seismometers are being filtered to produce a coherent estimate of the associated gravitational noise also known as Newtonian noise. The first implementation of the system uses a time-invariant (static) Wiener filter, which is the optimal filter for Newtonian-noise cancellation assuming that the noise is stationary. However, time variations in the form of transients and slow changes in correlations between sensors are possible and while time-variant filters are expected to cope with these variations better than a static Wiener filter, the question is what the limitations are of time-variant noise cancellation. In this study, we present a framework to study the performance limitations of time-variant noise cancellation filters and carry out a proof-of-concept with adaptive filters on seismic data at the Virgo site. We demonstrate that the adaptive filters, at least those with superior architecture, indeed significantly outperform the static Wiener filter with the residual noise remaining above the statistical error bound.