Power spectral density and similarity analysis of COVID-19 mortality waves across countries.

Background: During the COVID-19 pandemic, the Johns Hopkins University Center for Systems Science and Engineering (CSSE) established a comprehensive database detailing daily mortality rates across countries. This dataset revealed fluctuating global mortality trends attributable to COVID-19; however, the specific differences and similarities in mortality patterns between countries remain insufficiently explored. Consequently, this study employs Fourier and similarity analyses to examine these patterns within the frequency domain, thereby offering novel insights into the dynamics of COVID-19 mortality waves across different nations.

Low-field thoracic magnetic stimulation increases peripheral oxygen saturation levels in coronavirus disease (COVID-19) patients: A single-blind, sham-controlled, crossover study.

Severe acute respiratory syndrome coronavirus-2 may cause low oxygen saturation (SpO2) and respiratory failure in patients with coronavirus disease (COVID-19). Hence, increased SpO2 levels in COVID-19 patients could be crucial for their quality of life and recovery. This study aimed to demonstrate that a 30-minute single session of dorsal low-field thoracic magnetic stimulation (LF-ThMS) can be employed to increase SpO2 levels in COVID-19 patients significantly.

Modeling Post-Scratching Locomotion with Two Rhythm Generators and a Shared Pattern Formation.

This study aimed to present a model of post-scratching locomotion with two intermixed central pattern generator (CPG) networks, one for scratching and another for locomotion. We hypothesized that the rhythm generator layers for each CPG are different, with the condition that both CPGs share their supraspinal circuits and their motor outputs at the level of their pattern formation networks. We show that the model reproduces the post-scratching locomotion latency of 6.

Improved detection of magnetic signals by a MEMS sensor using stochastic resonance.

We introduce the behavior of the electrical output response of a magnetic field sensor based on microelectromechanical systems (MEMS) technology under different levels of controlled magnetic noise. We explored whether a particular level of magnetic noise applied on the vicinity of the MEMS sensor can improve the detection of subthreshold magnetic fields. We examined the increase in the signal-to-noise ratio (SNR) of such detected magnetic fields as a function of the magnetic noise intensity.

Digital signal processing by virtual instrumentation of a MEMS magnetic field sensor for biomedical applications.

We present a signal processing system with virtual instrumentation of a MEMS sensor to detect magnetic flux density for biomedical applications. This system consists of a magnetic field sensor, electronic components implemented on a printed circuit board (PCB), a data acquisition (DAQ) card, and a virtual instrument. It allows the development of a semi-portable prototype with the capacity to filter small electromagnetic interference signals through digital signal processing.

Respiratory magnetogram detected with a MEMS device.

Magnetic fields generated by the brain or the heart are very useful in clinical diagnostics. Therefore, magnetic signals produced by other organs are also of considerable interest. Here we show first evidence that thoracic muscles can produce a strong magnetic flux density during respiratory activity, that we name respiratory magnetogram.