A Class-E-Based AC-DC converter for PFC applications

Connection of nonlinear utility load har increased through resent years and is expected to continue increasing. Nonlinear utility load injects harmonic content into the grid and reduces voltage quality for nearby consumers. To limit harmonic content from nonlinear load, the International Electrotechnical Commission requires power supplies to be designed according to IEC 61000-3-2. Fulfilling this standard for nonlinear load is done by power factor correction (PFC). Conventionally, pulse width modulation (PWM) converter has been used for PFC converters as they provide high efficiency with a simple control technic. However, as PWM converters switch by hard-switching, that limits the switching frequency through switching loss and generates EMI, resonant converters has become more attractive. Resonant converters operate at soft-switching where the voltage across and/ or current through is zero in the switching moment. This reduces switching loss and EMI, and allow for high switching frequency. High switching frequency is desired as it enables high power density. Through this thesis, two resonant converters using high switching frequency has been proposed. These converters are based on a Class-E converter as it has low noise and high efficiency when switching at high frequency. The thesis includes a mathematical model for both converts, simulation and experimental testing result. Result from testing differs from calculated and simulated values, and troubleshooting for one of the converters has been conducted. Through troubleshooting and a second test with changed parameters, the performance of the converter increased compared to the first test. Due to lack of time, the debugging process was not completed and will be a part of future work

ISARIC-COVID-19 dataset: A Prospective, Standardized, Global Dataset of Patients Hospitalized with COVID-19

The International Severe Acute Respiratory and Emerging Infection Consortium (ISARIC) COVID-19 dataset is one of the largest international databases of prospectively collected clinical data on people hospitalized with COVID-19. This dataset was compiled during the COVID-19 pandemic by a network of hospitals that collect data using the ISARIC-World Health Organization Clinical Characterization Protocol and data tools. The database includes data from more than 705,000 patients, collected in more than 60 countries and 1,500 centres worldwide. Patient data are available from acute hospital admissions with COVID-19 and outpatient follow-ups. The data include signs and symptoms, pre-existing comorbidities, vital signs, chronic and acute treatments, complications, dates of hospitalization and discharge, mortality, viral strains, vaccination status, and other data. Here, we present the dataset characteristics, explain its architecture and how to gain access, and provide tools to facilitate its use