The signal transmission module of a magnetic nanoparticle thermometer (MNPT) was established in this study to analyze the error sources introduced during the signal flow in the hardware system. The underlying error sources that significantly affected the precision of the MNPT were determined through mathematical modeling and simulation. A transfer module path with the minimum error in the hardware system was then proposed through the analysis of the variations of the system error caused by the significant error sources when the signal flew through the signal transmission module. In addition, a system parameter, named the signal-to-AC bias ratio (i.e., the ratio between the signal and AC bias), was identified as a direct determinant of the precision of the measured temperature. The temperature error was below 0.1 K when the signal-to-AC bias ratio was higher than 80 dB, and other system errors were not considered. The temperature error was below 0.1 K in the experiments with a commercial magnetic fluid (Sample SOR-10, Ocean Nanotechnology, Springdale, AR, USA) when the hardware system of the MNPT was designed with the aforementioned method.

The joint video expert team (JVET) is currently developing a new video coding standard called H.266/Versatile Video Coding (VVC). Compared with High Efficiency Video Coding (HEVC), VVC has added a variety of coding tools. These tools have greatly improved video compression efficiency and maintained a high level video quality. However, due to the increase in computational complexity, the encoding time is much longer than HEVC. We propose a prediction tool based on DenseNet (a convolutional neural network) to decrease the VVC coding complexity. We predict the probability that the edge of 4×4 blocks in each 64×64 block is the division boundary by Convolutional Neural Networks (CNN). Then, we skip the unnecessary rate distortion optimization (RDO) and speed up the coding by probability vectors in advance. The proposed method can reduce the coding complexity of 46.10% in VTM10.0 intra coding, while Bjøntegaard delta bit rate (BDBR) only increases by 1.86%. In the sequence with a resolution greater than 1080P, the acceleration efficiency can be at 64.81%, the BDBR loss only increased by 1.92%.

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Magnetic fluid hyperthermia, as a novel cancer treatment, requires precise temperature control at 315 K–319 K (42 °C–46 °C). However, the traditional temperature measurement method cannot obtain the real-time temperature in vivo, resulting in a lack of temperature feedback during the heating process. In this study, the feasibility of temperature measurement and feedback control using magnetic nanoparticles is proposed and demonstrated. This technique could be applied in hyperthermia. Specifically, the triangular-wave temperature measurement method is improved by reconstructing the original magnetization response of magnetic nanoparticles based on a digital phase-sensitive detection algorithm. The standard deviation of the temperature in the magnetic nanoparticle thermometer is about 0.1256 K. In experiments, the temperature fluctuation of the temperature measurement and feedback control system using magnetic nanoparticles is less than 0.5 K at the expected temperature of 315 K. This shows the feasibility of the temperature measurement method for temperature control. The method provides a new solution for temperature measurement and feedback control in hyperthermia.

There is much debate about whether the junction temperature or phosphor temperature is higher in white light-emitting diodes (LEDs). The main reason is that the junction and phosphor temperatures cannot be measured directly using traditional temperature measurement tools. In this study, a magnetic nanoparticle thermometer, a nondestructive and precise temperature measurement tool, is introduced and described in detail. The model, measurement principle, and experimental setup are described. The temperature of the phosphor layer and the top surface of the P-N junction in white LEDs was measured directly using the magnetic nanoparticle thermometer, and the results show that the phosphor layer temperature was higher than the chip top surface temperature at different input voltages, providing a reference for relative researchers.