Causes of Intensive Care Unit Admissions in Children with SARS-CoV-2: A Single-Centre Observational Study.

Background: The proportion of intensive care unit (ICU) admissions in children that have and have not been directly caused by SARS-CoV-2 remains unclear. The aim of the study is to analyse a cohort of children admitted to the ICU with SARS-CoV-2 and determine whether the infection was the primary cause of their hospitalisation, a significant contributor, a suspected accomplice, or an incidental finding. Methods: This was a retrospective observational study of all the children admitted to the ICU with SARS-CoV-2 from March 2020 to February 2022 from the South Moravia region. The aim of the study was to assess whether the hospitalisation was likely to be directly caused by the virus (i.e., patients with acute COVID-19; the COVID group), whether the virus was a significant contributor to the hospitalisation (i.e., patients with multisystem inflammatory syndrome in children due to COVID-19; the MIS-C group), whether it may have contributed to the worsening of their underlying disease (the WORSENING group), or whether it was an incidental finding very likely unrelated to hospitalisation where SARS-CoV-2 positivity merely placed patients in the COVID-19 unit (the ISOLATION group). The groups were compared using a series of secondary outcomes. Results: The study population represented 150 paediatric ICU cases (age 8.6; IQR 3.5−13.3 years), with 66.7% being male. The COVID group represented 32.7% of cases (49/150); MIS-C, 30% (45/150); WORSENING, 14.7% (22/150); and ISOLATION, 22.7% (34/150). The median length of hospitalisation was found for the MIS-C group (11 days; 9 days in the ICU), the COVID group (6 days; five days in the ICU), WORSENING group (4.5 days; 4.5 days in the ICU) and the ISOLATION group (5.5 days; 3.5 days in the ICU), where the difference was significant (p < 0.001). Asymptomatic and mild cases were most common in the WORSENING (36.4% and 63.6%) and ISOLATION (52.9% and 44.1%) groups. Severe and critical cases were only present in the COVID (6.1% and 12.2%) and MIS-C (4.4% and 11.1%) groups; the severity difference was significant (p < 0.001). The groups did not differ significantly in the proportion of complete recovery and short- and long-term sequelae (p = 0.09). Conclusions: Patients with acute COVID-19 accounted for one-third of all ICU admissions, patients with MIS-C accounted for approximately another third, patients with worsening underlying disease accounted for 15%, and patients with incidental findings of SARS-CoV-2 positivity accounted for one-fifth of ICU admissions. A more significant disease was seen with acute COVID-19 and MIS-C.

Fluctuations of focused electron beam in a conventional SEM.

Noise diagnostics was performed on a tungsten hairpin cathode that was used in conventional scanning electron microscope (SEM) which operates in a high vacuum. The focused beam was firstly measured and its power spectrum obtained in order to characterize its slope in the lower frequencies which are connected with the events occurring on the cathode surface during the emission of electrons. Further experiments involved additional noise measurements which evaluated electron beam with altering beam energy, in particular at 5 kV, 10 kV and 20 kV up to 30 kV; with and without electron beam scanning involved and with different levels of cathode heating. Obtained results were evaluated in relation to a 1/f type noise component, generation-recombination process on the cathode surface, on the shot noise and on the velocity fluctuations caused by the ion oscillations. Achieved results were discussed.

New automatic localization technique of acoustic emission signals in thin metal plates.

In acoustic emission (AE) measurement, the information of the arrival time is very important for event location, event identification and source mechanism analysis. Manual picks are time-consuming and sometimes subjective, especially in the case of large volumes of digital data. Various techniques have been presented in the literature and are routinely used in practice such as amplitude threshold, analysis of the long-term average/short-term average (LTA/STA), high-order statistics or artificial neural networks. A new automatic determination technique of the first arrival times of AE signals is presented for thin metal plates. Based on Akaike's information criterion, proposed algorithm of the first arrival detection uses a specific characteristic function, which is sensitive to change of frequency in contrast to others such as envelope of the signal. The approach is applied to data sets of three different tests. Reliable results show the potential of our approach.