Three-axis components of magnetocardiography (MCG) signals are measured with a high sensitivity tunnel magnetoresistance (TMR) sensor in this paper. From the measurement result, the R-wave and QRS-complex of MCG associated with the cardiac cycle are clearly observable without need of averaging. The T-wave is at the noise level and the weaker P-wave is drowned in noise. It is a great progress comparing with previous MCG measurement with TMR sensor, where averaging was required to reliably detect R-wave. The amplitude of R-peak observed by the TMR sensor in x direction is 200 pT, which is consistent with the measurement of superconducting quantum interference device (SQUID) considering the effect of distance from the observation point to the magnetic field source. The y and z components R-peak are about 550 pT. As the TMR sensor can measure MCG at room temperature, potentially it is a promising alternative to cryogenically-cooled superconducting devices to make inexpensive MCG instrumentation for extensive clinical applications.

This study presents an algorithm for shrimp counting using a small-scale labeling model. The aim is to enhance shrimp farming efficiency, reduce biosecurity risks, and minimize manual counting errors. Experimental evaluations were conducted using Litopenaeus vannamei samples divided into four growth stages. A comparison was made between the classical threshold segmentation method, small-scale labeling density estimation based on FamNet, and our proposed small-scale labeling density estimation based on FamNet-S models. The results showed that the proposed FamNet-S-based small-scale labeling density estimation method achieved a better level of accuracy than the classical FamNet model across different growth stages. In the first stage, it reduced the mean absolute error (MAE) by 8.7% and the mean squared error (MSE) by 9.6%. In the fourth stage, MAE and MSE further decreased by 18.9% and 21.6%, respectively. The research findings demonstrate that the small-scale labeling density estimation approach based on FamNet-S exhibits robust adaptability and accuracy across diverse growth stages, rendering it suitable for scenarios with limited annotated samples. It effectively tackles challenges associated with shrimp overlap and occlusion while mitigating interference from feed and excrement, thus enhancing the precision and efficiency of shrimp counting. This algorithm for small-scale labeling density estimation significantly reduces annotation workloads while facilitating rapid deployment, making it an ideal solution for counting and marking in practical aquaculture environments. The study provides a high-precision yet efficient methodology for shrimp counting and marking tasks, thus reducing labor intensity while improving farming management accuracy, thereby supporting intelligent control in shrimp farming.

Magnetic nanoparticle imaging (MPI) is an emerging non-invasive technique with potential applications in bio-medical diagnostic and material science. In this paper, we propose a new method for MPI using tunnel magnetoresistance (TMR) sensor with an area of dimensions 0.45 mm*0.45 mm. The small size of the sensor promotes high level of integration and fine spatial resolution for magnetic field measurements. A solenoid excitation coil carrying alternating current is used to magnetize the magnetic nanoparticles (MNPs). We used commercial MNPs solution named synomag®-D with iron concentration 10 mg/ml as sample. The response of the MNPs is measured by the TMR sensor during a 2D raster scan resulting in a magnetic image. In order to eliminate the negative effect of the strong background field from the excitation coil, a compensation coil which is located close to the TMR sensor is utilized to subtract the background signal in situ during measurements. Comparing the experimental results with and without the compensation scheme shows that the setup with the compensation coil cancels 95% of the background signal and increases the signal to noise ratio (SNR) from 7 dB to 10 dB. Mainly considering the tradeoff of 1/f noise and the MNPs response to the excitation frequency, the operating frequencies of 135 Hz, 235 Hz and 335 Hz were investigated in this study. Experimental results show that the system is capable of imaging 5 μL MNPs solution with a 5 mm lift-off from the sensor to the top surface of the MNPs sample. Furthermore, an ‘L’ shape formed by 6 holes with 1 μL MNPs solution in each is imaged by the system. In comparison, it is very challenging for conventional MPI with coils as pickup sensors to image 10 μg irons in 1 μL MNPs solution at the low operating frequency. This is because TMR sensor has much better sensitivity than coils in the low frequency range. This work demonstrates the feasibility of using small TMR sensor with an excitation-compensation scheme for MPI. The advantages of high sensitivity, fine spatial resolution and low cost of the probe make it a promising alternative for future bio-medical research to measure the 3-D location and concentration of magnetic nanoparticles.

In response to the challenges posed by the complexity and potential hazards of traditional chemical methods for detecting the surface density of carbon fiber prepreg materials, this paper explores the use of eddy current testing principles. It establishes the relationship between coil impedance variation and the surface density of carbon fiber prepreg materials and designs a quadrupolar excitation eddy current detection probe. This probe can detect the surface density of both single-line and woven carbon fiber prepreg structures. The overall structure and dimensions of the designed quadrupolar probe were optimized using finite element simulation software. The results show that the number of coil turns significantly affects the sensor performance, with more turns leading to increased sensitivity. Moreover, with the same number of coil turns, smaller inner diameters and larger outer diameters of the coil enhance sensor sensitivity. A comprehensive comparison between unidirectional and woven carbon fiber models suggests that woven structures have superior electrical conductivity at identical excitation frequencies, while unidirectional models show more pronounced electrical anisotropy. These findings provide valuable insights for analyzing electrical properties, numerical simulations, and eddy current testing in composite materials.

A low-Tc dc SQUID placed in a superconducting and magnetic shield is insensitive to magnetic interference, but not completely immune to the effects of radio frequency interference (RFI). Here, we investigated the effect of two orthogonal RF fields on the second-order axial gradiometer's transfer characteristics and noise characteristics. RF field induced phase shift of the V - Φ curve. The modulated spikes of RF field on the V - Φ curve and noise spectrum became significant with the RF field increasing. The white noise of the system increased to 12.5 fT/√Hz with +10 dB axial RF field, nearly one and a half times of 8.5 fT/√Hz without RFI. The working point jumping occurred under the radial RF field of +5 and +10 dB, and the white noise increased to 17.2 and 165.8 fT √Hz, respectively. The reason of work point drift related to the magnetic flux coupling between the SQUID and pickup coil needs further studies.