Research on aeromagnetic data error analysis and processing of multi-rotor UAV based on variational mode decomposition algorithm.

Aeromagnetic survey of multi-rotor UAV is widely used in small and medium-sized mineral resources survey, engineering investigation, non-explosive detection and other fields due to its advantages of high safety, low cost and convenient operation. The original data of UAV aeromagnetic survey includes interference from external environment, interference from UAV platform and interference from airborne electromagnetic equipment. The interference is mainly shown as striping anomaly along the direction of the survey line in the aeromagnetic anomaly map, which affects the accuracy of aeromagnetic compensation and information detection of geological anomaly body, thus affecting the accuracy of interpretation of geological anomaly body.

Incipient fault diagnosis for the cam-driven absolute gravimeter.

The vibration disturbance caused by incipient faults is an important factor affecting the measurement accuracy of the cam-driven absolute gravimeter. Based on the characteristics of the cam-driven absolute gravimeter, such as the small amplitude of the incipient faults, the inadequate representation of features for the faults, and hard-to-find in the noise, a novel method for incipient fault diagnosis of the cam-driven absolute gravimeter is put forward in this paper, which integrates the parameter-optimized Variational Mode Decomposition (VMD) with Light Gradient Boosting Machine (LightGBM). The sparrow search algorithm is used to optimize the VMD parameters.

Vision Transformer-based recognition of diabetic retinopathy grade.

Background: In the domain of natural language processing, Transformers are recognized as state-of-the-art models, which opposing to typical convolutional neural networks (CNNs) do not rely on convolution layers. Instead, Transformers employ multi-head attention mechanisms as the main building block to capture long-range contextual relations between image pixels. Recently, CNNs dominated the deep learning solutions for diabetic retinopathy grade recognition.

Differential proteomic analysis of children infected with respiratory syncytial virus.

Respiratory syncytial virus (RSV) infection is the main cause of lower respiratory tract infection in children. However, there is no effective treatment for RSV infection. Here, we aimed to identify potential biomarkers to aid in the treatment of RSV infection.

iTRAQ‑based proteomic analysis reveals potential regulatory networks in dust mite‑related asthma treated with subcutaneous allergen immunotherapy.

Asthma is one of the most common childhood chronic diseases worldwide. Subcutaneous immunotherapy (SCIT) is commonly used in the treatment of house dust mite (HDM)‑related asthma in children. However, the therapeutic mechanism of SCIT in asthma remains unclear.