Endoscopic Screening for Laryngotracheal Complications in Children Following Prolonged Mechanical Ventilation Maintained Through Endotracheal Intubation: A Cross-Sectional Pilot Project.

Background: An endoscopic screening program following successful weaning from prolonged mechanical ventilation maintained through endotracheal tube (ET; ) may be justified to assess the upper (laryngotracheal) airway in children who may not always be symptomatic for intubation-related complications.

Objectives: To evaluate effects of prolonged intubation in children through endoscopic screening of the laryngotracheal airway.

Methods: In this cross-sectional pilot project, children (2 months-12 years) successfully extubated following prolonged intubation were selected, irrespective of having symptoms, for a 1-time flexible nasolaryngoscopy at third to sixth month post-extubation (follow-up window).

Dominant higher-order vortex gyromodes in circular magnetic nanodots.

The transition to the third dimension enables the creation of spintronic nanodevices with significantly enhanced functionality compared to traditional 2D magnetic applications. In this study, we extend common two-dimensional magnetic vortex configurations, which are known for their efficient dynamical response to external stimuli without a bias magnetic field, into the third dimension. This extension results in a substantial increase in vortex frequency, reaching up to 5 GHz, compared to the typical sub-GHz range observed in planar vortex oscillators.

AI as a user of AI: Towards responsible autonomy.

Recent advancements in Artificial Intelligence (AI), particularly in generative language models and algorithms, have led to significant impacts across diverse domains. AI capabilities to address prompts are growing beyond human capability but we expect AI to perform well also as a prompt engineer. Additionally, AI can serve as a guardian for ethical, security, and other predefined issues related to generated content.

Artificial intelligence centric scientific research on COVID-19: an analysis based on scientometrics data.

With the spread of the deadly coronavirus disease throughout the geographies of the globe, expertise from every field has been sought to fight the impact of the virus. The use of Artificial Intelligence (AI), especially, has been the center of attention due to its capability to produce trustworthy results in a reasonable time. As a result, AI centric based research on coronavirus (or COVID-19) has been receiving growing attention from different domains ranging from medicine, virology, and psychiatry etc.

A Novel Smart City-Based Framework on Perspectives for Application of Machine Learning in Combating COVID-19.

The spread of COVID-19 worldwide continues despite multidimensional efforts to curtail its spread and provide treatment. Efforts to contain the COVID-19 pandemic have triggered partial or full lockdowns across the globe. This paper presents a novel framework that intelligently combines machine learning models and the Internet of Things (IoT) technology specifically to combat COVID-19 in smart cities.

Voltage-Controlled Magnetic Anisotropy in FeCo/Pd/MgO system.

Voltage-controlled magnetic anisotropy (VCMA) in an epitaxially grown Fe/FeCo/Pd/MgO system was investigated using spin-wave spectroscopy. The spin-wave resonant frequency linearly depended on the bias-voltage. The resonant-frequency shift increased with the Co fraction in FeCo/Pd.