Publications by authors named "E J Popovici"

Energy efficiency constitutes a pivotal performance indicator for 5G New Radio (NR) networks and beyond, and achieving optimal efficiency necessitates the meticulous consideration of trade-offs against other performance parameters, including latency, throughput, connection densities, and reliability. Energy efficiency assumes it is of paramount importance for both User Equipment (UE) to achieve battery prologue and base stations to achieve savings in power and operation cost. This paper presents an exhaustive review of power-saving research conducted for 5G and beyond 5G networks in recent years, elucidating the advantages, disadvantages, and key characteristics of each technique.

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Purpose: The COVID-19 pandemic has severely impacted healthcare workers, a professional category at risk of infection in both hospital and community settings. The aim of the study was to compare morbidity among hospital staff and that in general population, as well as the factors predicting non-vaccination and reinfection.

Patients And Methods: The present study is a retrospective, cross-sectional study.

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Objective: To report our step-by-step technique for 3D laparoscopic radical nephrectomy and thrombectomy for a right renal tumor with level IV venous thrombus. Worldwide experience in minimally-invasive approach for such complex cases is limited.

Materials And Methods: A 66-year-old male was incidentally diagnosed with a right renal tumor.

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Article Synopsis
  • A systematic review was conducted to analyze the impact of short-term ozone exposure on COVID-19 transmission and progression, covering studies from January 2020 to January 2023.
  • The review identified 18 relevant studies across eight countries, revealing a mixed association between ozone levels and COVID-19 incidence, severity, and mortality.
  • Results indicated that while some studies showed higher ozone exposure linked to increased COVID-19 cases, severity, and deaths, others reported negative or no significant associations, suggesting a nuanced relationship that may vary by region.
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Article Synopsis
  • The study introduces a new method that allows healthcare professionals to use sound to detect neonatal seizures through EEG analysis, making interactions with AI decision support more intuitive.
  • Traditional EEG interpretation requires specialized expertise, which is often unavailable; this method enables faster analysis—turning an hour of data into just five seconds—while maintaining accuracy comparable to experienced neurophysiologists.
  • By combining AI algorithms with human-centered approaches, the method allows less experienced healthcare providers to better understand seizure events through sound, demonstrating improved performance when AI is used alongside medical professionals.
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