Topographically specific sleep spindles show distinctive thalamocortical network behaviors.

This study presents a detailed fabrication method, together with validation, discussion, and analysis, for state-of-the-art silicon carbide (SiC) etching of vertical and bevelled structures by using inductively coupled plasma reactive ion etching (ICP-RIE) for microelectronic applications. Applying different gas mixtures, a maximum bevel angle of 87° (almost vertical), large-angle bevels ranging from 40° to 80°, and small-angel bevels ranging from 7° to 17° were achieved separately using distinct gas mixtures at different ratios. We found that SF6 with additive O2 was effective for vertical etching, with a best etching rate of 3050 Å/min. As for the large-angle bevel structures, BCl3 + N2 gas mixtures show better characteristics, exhibiting a controllable and large etching angle range from 40° to 80° through the adjustment of the mixture ratio. Additionally, a Cl2 + O2 mixture at different ratios is applied to achieve a small-angel bevels ranging from 7° to 17°. A minimum bevel angel of approximately 7° was achieved under the specific volume of 2.4 sccm Cl2 and 3.6 sccm O2. These results can be used to improve performance in various microelectronic applications including MMIC via holes, PIN diodes, Schottky diodes, JFETs’ bevel mesa, and avalanche photodiode fabrication.

The mouse model is an important research tool in neurosciences to examine brain function and diseases with genetic perturbation in different brain regions. However, the limited techniques to map activated brain regions under specific experimental manipulations has been a drawback of the mouse model compared to human functional brain mapping. Here, we present a functional brain mapping method for fast and robust in vivo brain mapping of the mouse brain. The method is based on the acquisition of high density electroencephalography (EEG) with a microarray and EEG source estimation to localize the electrophysiological origins. We adapted the Fieldtrip toolbox for the source estimation, taking advantage of its software openness and flexibility in modeling the EEG volume conduction. Three source estimation techniques were compared: Distribution source modeling with minimum-norm estimation (MNE), scanning with multiple signal classification (MUSIC), and single-dipole fitting. Known sources to evaluate the performance of the localization methods were provided using optogenetic tools. The accuracy was quantified based on the receiver operating characteristic (ROC) analysis. The mean detection accuracy was high, with a false positive rate less than 1.3% and 7% at the sensitivity of 90% plotted with the MNE and MUSIC algorithms, respectively. The mean center-to-center distance was less than 1.2 mm in single dipole fitting algorithm. Mouse microarray EEG source localization using microarray allows a reliable method for functional brain mapping in awake mouse opening an access to cross-species study with human brain.

In this paper, the extraction of the life activity spectrum based on the millimeter (mm) wave radar is designed to realize the detection of target objects and the threshold trigger module. The maximum likelihood estimation method is selected to complete the design of the average early warning probability trigger function. The threshold trigger module is designed for the echo signal of static objects in the echo signal. It will interfere with the extraction of Doppler frequency shift results. The moving target detection method is selected, and the filter is designed. The static clutter interference is filtered without affecting the phase difference between the detection sequences, and the highlight target signal is improved. The frequency and displacement of thoracic movement are used as the detection data. Through the Fourier transform calculation of the sequence, the spectrum value is extracted within the estimated range of the heartbeat and respiration spectrum, and the heartbeat and respiration signals are picked up. The proposed design uses Modelsim and Quartus for CO-simulation to complete the simulation verification of the function, extract the number of logical units occupied by computing resources, and verify the algorithm with the vital signs experiment. The heartbeat and respiration were detected using the sports bracelet; the relative errors of heartbeat detection were 0–6.3%, the respiration detection was 0–9.5%, and the relative errors of heartbeat detection were overwhelmingly less than 5%.

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