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Air bubbles in the upper ocean are generated mainly by waves breaking at the air–sea interface. As such, after the waves break, entrained air bubbles evolve in the form of plumes in the turbulent flow, exchange gas with the surrounding water, and may eventually rise to the surface. To shed light on the short-term response of entrained bubbles in different stormy conditions and to assess the link between bubble plume penetration depth, mechanical and thermal forcings, and the air–sea transfer velocity of CO2, a field experiment was conducted from an oceanographic research tower in the north Adriatic Sea. Air bubble plumes were observed using high-resolution echosounder data from an upward-looking 1000 kHz sonar. The backscatter signal strength was sampled at a high resolution, 0.5 s in time and 2.5 cm along the vertical direction. Time series profiles of the bubble plume depth were established using a variable threshold procedure applied to the backscatter strength. The data show the occurrence of bubbles organized into vertical plume-like structures, drawn downwards by wave-generated turbulence and other near-surface circulations, and reaching the seabed at 17 m depth under strong forcing. We verify that bubble plumes adapt rapidly to wind and wave conditions and have depths that scale approximately linearly with wind speed. Scaling with the wind–wave Reynolds number is also proposed to account for the sea-state severity in the plume depth prediction. Results show a correlation between measured bubble depths and theoretical air–sea CO2 transfer velocity parametrized with wind-only and wind/wave formulations. Further, our measurements corroborate previous results suggesting that the sinking of newly formed cold-water masses helps bring bubbles to greater depths than those reached in stable conditions for the water column. The temperature difference between air and sea seems sufficient for describing this intensification at the leading order of magnitude. The results presented in this study are relevant for air–sea interaction studies and pave the way for progress in CO2 gas exchange formulations.

The Mediterranean Sea is a primary source of food, ecosystem services and economic activities and one of the most active cyclogenetic regions in the world, where the influence of orographic and morphological features of the relatively small basin plays an important role. Together with the explosive cyclogenesis, tropical-like cyclones (also called Mediterranean Hurricanes or Medicanes) are among the strongest types of storms that can be found in the Mediterranean basin, occurring predominantly in the Ionian, Balearic and Tyrrhenian sub-basins. Similarly to tropical cyclones (Hurricanes or Typhoons), these cyclonic structures are characterized by strong rotating and translating wind fields, which often lead to a combination of remotely generated swell waves and locally generated wind waves, often referred to as crossing sea states. Despite the well-known potential of Medicanes to cause significant damage near islands and coastal zones, which is predicted to intensify as a result of climate change, to date the characterization of maximum individual waves generated during these events is still lacking. In this study, we carry out the first analysis of the large-scale geographical distribution of wave maxima within the wave fields generated during three recent Medicane events using the WAVEWATCH III® spectral wave model forced by ERA5 reanalysis winds, also investigating the influence of crossing sea states on the maximum wave amplitudes with novel statistical formulations developed for such conditions. Our results show that, as in the case of tropical cyclones, several regions of the cyclone field are characterized by crossing sea states, whose role in the formation of the maximum individual waves occurring near the eye of the storm was found to be confined. Furthermore, extreme wave predictions accounting for the local crossing conditions yield differences up to 5% compared to standard statistical distributions.

The study of extreme ocean waves has gained considerable interest in recent years, due to their importance for offshore design and navigation safety, and several theoretical approaches have been developed for their statistical description. However, in the case of crossing seas, where two or more wave systems of different characteristics are present, a full understanding of the main physical mechanisms responsible for the occurrence of very high individual waves is still lacking. As a consequence, the prediction of extremes in such conditions currently relies on integrated parameters of the total sea state, such as the spectral wave steepness. In this study, to gain further insight into the role of the crossing wind sea and swell wave systems in producing extreme individual waves, we investigate realistic sea states during typhoon Kong-rey (2018) using an ensemble of numerical simulations obtained from a phase-resolving wave model based on the High-Order Spectral (HOS) method. The reliability of the numerical fields is assessed for the first time with stereo wave measurements of the sea surface elevation field collected from an offshore platform in the area of interest. We show that, in specific conditions, space-time extreme crest heights in crossing seas can be larger than in unimodal seas due to second-order bound wave interactions between the wind sea and the swell. To improve existing prediction capabilities, we propose a novel formulation for the wave steepness in crossing seas, which includes nonlinear effects up to the second order and accounts for the spectral parameters of the interacting wave systems.

IntroductionIn hospitalized patients with COVID-19, bloodstream infections (BSI) are associated with high mortality and high antibiotic resistance rates. The aim of this study was to describe BSI etiology, antimicrobial resistance profile and risk factors in a sample of patients deceased with COVID-19 from the Italian National COVID-19 surveillance.MethodsHospital charts of patients who developed BSI during hospitalization were reviewed to describe the causative microorganisms and their antimicrobial susceptibility profiles. Risk factors were analyzed in univariate and multivariate analyses.ResultsThe study included 73 patients (71.2% male, median age 70): 40 of them (54.8%) received antibiotics and 30 (41.1%) systemic steroids within 48 h after admission; 53 (72.6%) were admitted to intensive care unit. Early steroid use was associated with a significantly shorter interval between admission and BSI occurrence. Among 107 isolated microorganisms, the most frequent were Enterococcus spp., Candida spp., Acinetobacter baumannii, and Klebsiella pneumoniae. Median time from admission to BSI was shorter for Staphylococcus aureus compared to all other bacteria (8 vs. 24 days, p = 0.003), and longer for Enterococcus spp., compared to all other bacteria (26 vs. 18 days, p = 0.009). Susceptibility tests showed a high rate of resistance, with 37.6% of the bacterial isolates resistant to key antibiotics. Resistance was associated with geographical area [adjusted odds ratio (AOR) for Central/South Italy compared to North Italy: 6.775, p = 0.002], and with early use of systemic steroids (AOR 6.971, p = 0.018).ConclusionsIn patients deceased with COVID-19, a large proportion of BSI are caused by antibiotic-resistant bacteria. Early steroid use may facilitate this occurrence.

Accurate wind-wave forecasting in enclosed and semi-enclosed basins is a challenging task, demanding primarily for high-resolution wind forcing at regional scale. This is generally obtained with dynamical downscaling from a low-to-mid resolution atmospheric model. In this context, a new wave forecasting system for the marginal Adriatic Sea is herein presented aimed at proposing an alternative strategy for accurate wind-wave forecasting in (semi-) enclosed basins that does not require an ad-hoc regional atmospheric model. The system is based on the state-of-the-art WAVEWATCH III® spectral wave model forced by the global IFS-ECMWF forecast. At first, wind speed is quantile-corrected to account for the systematic underestimation over the Adriatic Sea. Then, the significant wave height in the target region and for regimes associated with marine storms is calibrated following standard procedure. Wind and wave observations from different sources are used for calibration and validation of the wave forecasts, which achieve satisfactory scores. We also compare results with those of other forecasting systems in the area, highlighting the importance of the wind forcing accuracy and the wave model calibration. Doing so, we discuss the challenges that characterise (semi-) enclosed environments in order to propose effective solutions for them and future developments.

Measurement(s) atmospheric wind direction • atmospheric wind speed • wave Technology Type(s) weather station • acoustic AWAC system • waverider buoy • Camera Device Sample Characteristic - Environment coastal sea water Sample Characteristic - Location Adriatic Sea Machine-accessible metadata file describing the reported data: https://doi.org/10.6084/m9.figshare.13415780

Abstract Background A history of previous cardiac disease increases the maternal mortality risk by as much as 100%. There is no consensus on the absolute contraindications to vaginal delivery in valvular heart disease, but central regional anesthesia is traditionally considered contraindicated in patients with severe aortic stenosis. Case presentation A 29-year-old primigravid woman with severe aortic stenosis was admitted to the obstetrics department for programmed labor induction. With epidural anesthesia and mini-invasive hemodynamic monitoring labor and operative vaginal delivery were well tolerated, and hemodynamic stability was always maintained. Conclusions Epidural analgesia and oxytocin induction are possible for the labor management of parturients with severe aortic stenosis given that continuous non-invasive followed by invasive hemodynamic monitoring can be provided and given the absence of any obstetric or cardiologic contraindications and the strong will of the patient.

Abstract Background Rapid neuromuscular block reversal at the end of major abdominal surgery is recommended to avoid any postoperative residual block. To date, no study has evaluated sugammadex performance after rocuronium administration in patients undergoing liver transplantation. This is a randomized controlled trial with the primary objective of assessing the neuromuscular transmission recovery time obtained with sugammadex versus neostigmine after rocuronium induced neuromuscular blockade in patients undergoing orthotopic liver transplantation. Methods The TOF-Watch SX®, calibrated and linked to a portable computer equipped with TOF-Watch SX Monitor Software®, was used to monitor and record intraoperative neuromuscular block maintained with a continuous infusion of rocuronium. Anaesthetic management was standardized as per our institution’s internal protocol. At the end of surgery, neuromuscular moderate block reversal was obtained by administration of 2 mg/kg of sugammadex or 50 mcg/kg of neostigmine (plus 10 mcg/kg of atropine). Results Data from 41 patients undergoing liver transplantation were analysed. In this population, recovery from neuromuscular block was faster following sugammadex administration than neostigmine administration, with mean times±SD of 9.4 ± 4.6 min and 34.6 ± 24.9 min, respectively (p

Climbing plants require an external support to grow vertically and enhance light acquisition. Climbers that find a suitable support demonstrate greater performance and fitness than those that remain prostrate. Support search is characterized by oscillatory movements (i.e., circumnutation), in which plants rotate around a central axis during their growth. Numerous studies have elucidated the mechanistic details of circumnutation, but how this phenomenon is controlled during support searching remains unclear. To fill this gap, here we tested whether simulation-based machine learning methods can capture differences in movement patterns nested in actual kinematical data. We compared machine learning classifiers with the aim of generating models that learn to discriminate between circumnutation patterns related to the presence/absence of a support in the environment. Results indicate that there is a difference in the pattern of circumnutation, depending on the presence of a support, that can be learned and classified rather accurately. We also identify distinctive kinematic features at the level of the junction underneath the tendrils that seems to be a superior indicator for discerning the presence/absence of the support by the plant. Overall, machine learning approaches appear to be powerful tools for understanding the movement of plants.

A climatology of the wind waves in the Mediterranean Sea is presented. The climate patterns, their spatio-temporal variability and change are based on a 40-year (1980–2019) wave hindcast, obtained by combining the ERA5 reanalysis wind forcing with the state-of-the-art WAVEWATCH III spectral wave model and verified against satellite altimetry. Results are presented for the typical (50th percentile) and extreme (99th percentile) significant wave height and, for the first time at the regional Mediterranean Sea scale, for the typical and extreme expected maximum individual wave height of sea states. The climate variability of wind waves is evaluated at seasonal scale by proposing and adopting a definition of seasons for the Mediterranean Sea states that is based on the satellite altimetry wave observations of stormy (winter) and calm (summer) months. The results, initially presented for the four seasons and then for winter and summer only, show the regions of the basin where largest waves occur and those with the largest temporal variability. A possible relationship with the atmospheric parameter anomalies and with teleconnection patterns (through climate indices) that motivates such variability is investigated, with results suggesting that the Scandinavian index variability is the most correlated to the Mediterranean Sea wind-wave variability, especially for typical winter sea states. Finally, a trend analysis shows that the Mediterranean Sea typical and extreme significant and maximum individual wave heights are decreasing during summer and increasing during winter.