Since December 2019, Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has caused millions of deaths and seriously threatened the safety of human life; indeed, this situation is worsening and many people are infected with the new coronavirus every day. Therefore, it is very important to understand patients’ degree of infection and infection history through antibody testing. Such information is useful also for the government and hospitals to formulate reasonable prevention policies and treatment plans. In this paper, we develop a lateral flow immunoassay (LFIA) method based on superparamagnetic nanoparticles (SMNPs) and a giant magnetoresistance (GMR) sensing system for the simultaneously quantitative detection of anti-SARS-CoV-2 immunoglobulin M (IgM) and G (IgG). A simple and time-effective co-precipitation method was utilized to prepare the SMNPs, which have good dispersibility and magnetic property, with an average diameter of 68 nm. The Internet of Medical Things-supported GMR could transmit medical data to a smartphone through the Bluetooth protocol, making patient information available for medical staff. The proposed GMR system, based on SMNP-supported LFIA, has an outstanding advantage in cost-effectiveness and time-efficiency, and is easy to operate. We believe that the suggested GMR based LFIA system will be very useful for medical staff to analyze and to preserve as a record of infection in COVID-19 patients.

Road traffic sign detection and recognition play an important role in advanced driver assistance systems (ADAS) by providing real-time road sign perception information. In this paper, we propose an improved (Single Shot Detector) SSD algorithm via multi-feature fusion and enhancement, named MF-SSD, for traffic sign recognition. First, low-level features are fused into high-level features to improve the detection performance of small targets in the SSD. We then enhance the features in different channels to detect the target by enhancing effective channel features and suppressing invalid channel features. Our algorithm gets good results in domestic real-time traffic signs. The proposed MF-SSD algorithm is evaluated with the German Traffic Sign Recognition Benchmark (GTSRB) dataset. The experimental results show that the MF-SSD algorithm has advantages in detecting small traffic signs. Compared with existing methods, it achieves higher detection accuracy, better efficiency, and better robustness in complex traffic environment.

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A novel method is proposed to fabricate micro Diffractive Optical Elements (DOE) using micro cutting tools shaped with focused ion beam (FIB) milling. Micro tools with nanometric cutting edges and complicated shapes are fabricated by controlling the tool facet's orientation relative to the FIB. The tool edge radius of less than 30 nm is achieved for the nano removal of the work materials. Semi-circular micro tools and DOE-shaped micro tools are developed to fabricate micro-DOE and sinusoidal modulation templates. Experiments show that the proposed method can be a high efficient way in fabricating micro-DOE with nanoscale surface finishes.

Currently, cardiovascular diseases become one of the major threat to human's life. The early prevention of cardiovascular diseases plays a critical role in the healthcare engineering. Point of care monitoring the blood lipid level is capable of making the positive contribution to the prevention of cardiovascular disease. Ubiquitous smartphones paved the way as the flexible and widespread platform for the interaction of various health information. In this manuscript, we report the world's first medical smartphone as an electrochemical analyzer for blood lipid monitoring. Integrating an electrochemical analyzer into a smartphone allows us to measure the current generated by the enzymatic reaction with the total cholesterol test strip. The disposable test strip is used to convert the biochemical signal to electrical signal through the electrochemical reaction. The proposed medical smartphone can provide accurate evaluation of patient's blood lipid level as compared to the clinical biochemical analyzer. The proposed medical smartphone system is a promising platform as a point-of-care device for blood total cholesterol (TC) monitoring, which can be applied for long-term prevention of cardiovascular disease due to its portability, reliability, lower cost, convenience, and internet-based medical data interaction.