arXiv subjects

Guoping Gao

Publications and source records attributed to Guoping Gao.

3 recordsLinked to original sources

arXiv2023

Stability Improvement of Nuclear Magnetic Resonance Gyroscope with Self-Calibrating Parametric Magnetometer

In this paper, we study the stability of nuclear magnetic resonance gyroscope (NMRG), which employs Xe nuclear spins to measure inertial rotation rate. The Xe spin polarization is sensed by an in-situ Rb-magnetometer. The Rb-magnetometer works in a parametric oscillation mode (henceforth referred to as the Rb parametric magnetometer, or Rb-PM), in which the Larmor frequency of the Rb spins is modulated and the transverse components of Xe nuclear spin polarization are measured. As the measurement output of the Rb-PM, the phase of the Xe nuclear spin precession is eventually converted to the Xe nuclear magnetic resonance (NMR) frequencies and the inertial rotation rate. Here we provide a comprehensive study of the NMR phase measured by the Rb-PM, and analyze the influence of various control parameters, including the DC magnetic field, the frequency and phase of the modulation field, and the Rb resonance linewidth, on the stability of the NMR phase. Based on these analysis, we propose and implement a self-calibrating method to compensate the NMR phase drift during the Rb-PM measurement. With the self-calibrating Rb-PM, we demonstrate a significant improvement of the bias stability of NMRG.

physics.atom-ph↗

arXiv2020

MODMA dataset: a Multi-modal Open Dataset for Mental-disorder Analysis

According to the World Health Organization, the number of mental disorder patients, especially depression patients, has grown rapidly and become a leading contributor to the global burden of disease. However, the present common practice of depression diagnosis is based on interviews and clinical scales carried out by doctors, which is not only labor-consuming but also time-consuming. One important reason is due to the lack of physiological indicators for mental disorders. With the rising of tools such as data mining and artificial intelligence, using physiological data to explore new possible physiological indicators of mental disorder and creating new applications for mental disorder diagnosis has become a new research hot topic. However, good quality physiological data for mental disorder patients are hard to acquire. We present a multi-modal open dataset for mental-disorder analysis. The dataset includes EEG and audio data from clinically depressed patients and matching normal controls. All our patients were carefully diagnosed and selected by professional psychiatrists in hospitals. The EEG dataset includes not only data collected using traditional 128-electrodes mounted elastic cap, but also a novel wearable 3-electrode EEG collector for pervasive applications. The 128-electrodes EEG signals of 53 subjects were recorded as both in resting state and under stimulation; the 3-electrode EEG signals of 55 subjects were recorded in resting state; the audio data of 52 subjects were recorded during interviewing, reading, and picture description. We encourage other researchers in the field to use it for testing their methods of mental-disorder analysis.

cs.DL↗

arXiv2016

Molecule-Induced Conformational Change in Boron Nitride Nanosheets with Enhanced Surface Adsorption

Surface interaction is extremely important to both fundamental research and practical application. Physisorption can induce shape and structural distortion (i.e. conformational changes) in macromolecular and biomolecular adsorbates, but such phenomenon has rarely been observed on adsorbents. Here, we demonstrate theoretically and experimentally that atomically thin boron nitride (BN) nanosheets as an adsorbent experience conformational changes upon surface adsorption of molecules, increasing adsorption energy and efficiency. The study not only provides new perspectives on the strong adsorption capability of BN nanosheets and many other two-dimensional nanomaterials but also opens up possibilities for many novel applications. For example, we demonstrate that BN nanosheets with the same surface area as bulk hBN particles are more effective in purification and sensing.

cond-mat.mes-hall↗