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Magnetic anomaly detection is an effective method for detecting ferromagnetic targets. The practical application of target detection by measuring the magnetic gradient has been confirmed in many studies, and its suppression of background noise has been widely recognized. However, the variation of the unidirectional magnetic field gradient is very small in a short distance, and the amplitude of the signal is also affected by the direction of the target’s magnetic moment and the shaking of the sensor platform itself. These make it difficult to extract the signal from complex background interference. In order to solve these problems, this paper is devoted to use the variation of three axial magnetic gradients in the geomagnetic coordinate system caused by the presence of magnetic target (we call it full magnetic gradient) to construct the magnetic anomaly characteristic of the target. A set of orthonormal basis functions is further derived to linearly describe this characteristic, which improves the signal-to-noise ratio (SNR) of the signal from the perspective of signal energy. The present work main contribution is to propose a full magnetic gradient orthonormal basis function (FMG-OBF) method to effectively characterize magnetic anomaly of magnetic targets. Compared with the traditional one-direction magnetic gradient orthonormal basis function method, the SNR of this method is greatly improved, and it is not affected by a change in the target magnetic moment’s direction nor by the shaking of the sensor carrier platform. Therefore, it has great value in the practical application of aeromagnetic detection.

Pulmonary arterial hypertension (PAH) is a severe vascular disease that adversely affects patient health and can be life threatening. The present study aimed to investigate the detailed role of nuclear paraspeckle assembly transcript 1 (NEAT1) in PAH. Using RT‑qPCR, the expression levels of NEAT1, microRNA (miR)‑34a‑5p, and Kruppel‑like factor 4 (KLF4) were detected in both hypoxia‑treated pulmonary arterial smooth muscle cells (PASMCs) and serum from PAH patients. Then, the interactions among miR‑34a‑5p, NEAT1, and KLF4 were evaluated by dual‑luciferase reporter assay. The detailed role of the NEAT1/miR‑34a‑5p/KLF4 axis in PAH pathogenesis was further explored using MTT, Transwell, and western blot assays. The results revealed that NEAT1 targeted miR‑34a‑5p and miR‑34a‑5p targeted KLF4. In hypoxia‑treated PASMCs and serum from PAH patients, high NEAT1 and KLF4 expression levels and low miR‑34a‑5p expression were observed. The proliferation and migration of hypoxia‑treated PASMCs were reduced by transfection with sh‑NEAT1 or miR‑34a‑5p mimics. The suppressive effects of NEAT1 knockdown on the proliferation and migration of hypoxia‑treated PASMCs were reversed by knock down of miR‑34a‑5p expression and increased KLF4 expression. NEAT1 was not only highly expressed in the serum of PAH patients but its silencing also alleviated PAH by regulating miR‑34a‑5p/KLF4 in vitro. The present study highlighted a potential new therapeutic target and diagnostic biomarker for PAH.

A simple photonic crystal fiber (PCF) temperature sensor with high sensitivity based on the principle of surface plasmon resonance (SPR) is proposed. The cladding of the sensor is mainly composed of two layers of square arranged holes. The inner wall of the outer air holes is selectively plated with gold film, and the outer holes are filled with the temperature sensitive material chloroform to promote the coupling of the surface plasmon mode and the fundamental mode, thereby improving the sensitivity. The finite element method is used to analyze the effects of the temperature on the performance of the sensor. Through tailoring the structural parameters, it is shown that the maximum sensitivity of the sensor can reach up to −10.4 nm/℃ in the range of 0 ℃ to 60 ℃ with high resolution and good linearity. Such appealing characteristics make the sensor be one of the important potential candidates in the field of temperature sensing.

In performing the detection and tracking of ferromagnetic targets or magnetic anomaly detection, a magnetometer array or magnetic gradiometer is often used to suppress environmental background magnetic field interference and improve measurement accuracy. Increasing the distance between the magnetometers is beneficial to improving the signal-to-noise ratio(SNR) of the magnetometer gradiometer, but the mismatching error of the magnetometer array affects the measurement accuracy of the magnetic gradient tensor and the positioning accuracy of the ferromagnetic target. In order to calibrate the mismatch error of a magnetometer array, the mounting position and orientation of each magnetometer must be accurately measured. When the magnetometer installation array is too large, the commonly used calibration methods are difficult to implement because it is difficult to make such a large rigid support, optical systems or robot. This paper reports a method that uses two coils and an excitation current source to generate a test magnetic field, after which methods of modulation demodulation and phase-locked filtering are used to suppress the ambient magnetic field interference. The output of each magnetometer is recorded, and the Particle Swarm Optimization (PSO) algorithm is employed to calculate the mounting position and orientation of each magnetometer. After theoretical analysis, computational simulation, and experimental verification, the results showed that the position measurements in a range of 2.4 m × 2.4 m were accurate to within 0.05 m and the orientation measurements were accurate to within 0.03 radians. The average relative positioning error was less than 1.7%. By designing larger coils and current sources, the needs of larger arrays can be satisfied as long as the same SNR is maintained.

In this paper, two important sources of the non-orthogonal errors of triaxial magnetometers were analysed. The non-orthogonal error mainly come from the transverse sensitivity of uniaxial sensor or non-orthogonality between the three axes of magnetic magnetometer. These two error sources were separated by mathematical analysis. Then a two-step calibration method of triaxial magnetometers was designed. It showed that the peak-to-peak value of the calculated result of the scalar of magnetic field could be reduced to 56nT from 350nT within the range of 50000nT.

For an ultrasound device, to prolong its lifetime and guarantee the performance is of significant importance. Actually, it is difficult for a traditional piezoelectric ultrasound transducer to recover from physical damage caused by sudden impact, accidental scratches, and fatigue fracture. As a promising ultrasound device, the optoacoustic transducer, the cole part of which is inorganic-polymer nanocomposite, has drawn much attention in recent years. Fortunately, the development of self-healable polymer provides a good chance for us to endow this kind of device with self-healing capability. Here, based on a covalently cured poly(urea-urethane) elastomeric network and carbon nanotubes nanocomposite, we introduce a catalyst-free and room temperature self-healing optoacoustic transducer. Such device is designed to have a three-layered structure——self-healing nanocomposite/PDMS/glass. By taking the advantage of the principle of wave superposition, its laser-generated ultrasound can be enhanced greatly. This novel ultrasound transducer behaves excellent self-healing performance, and it can recover from a cut or laser-induced damage. After 10th self-repairs, its output can still maintain 92.3% of the original sound pressure. With a self-focusing technology, the developed device can produce high intensity ultrasound (29.2 MPa); after a self-healing process, its laser-generated ultrasound can be kept as high as 28.7 MPa, which is comparable to those values reported in previous literatures with the same laser energy input. Most importantly, such high intensity ultrasound can be successfully used for thrombolysis. These promising results demonstrate that the obtained self-healing ultrasound device is suitable for biomedical applications, which may open a new path for smart biomedical device design and fabrication in the future.