Synthesis and Mechanism Study of an Environmental Additive Used in Water-Based Drilling Fluids from Bovine Bone Glue.

At present, animal bone glue has been widely used in industry, but there are no relevant research reports on its application in the petroleum industry. In this paper, the rheological properties, inhibition, filtration, and temperature resistance performance of modified bone glue (Mbg) were evaluated in water-based drilling fluids, and the results showed that Mbg can significantly affect the performance of water-based muds with minimal dosage, and temperature resistance of Mbg could reach up to 130 °C. The inhibition mechanism of Mbg in drilling fluids was investigated by infrared spectroscopy (FT-IR), X-ray diffraction (XRD), zeta potential, thermogravimetric analysis (TGA), and scanning electron microscope (SEM).

Prediction of IGBT Gate Oxide Layer's Performance Degradation Based on MultiScaleFormer Network.

Insulated gate bipolar transistors (IGBTs) are widely used in power electronic devices, and their health prediction problems have attracted much attention in the field of power electronic equipment health management. The performance degradation of IGBT gate oxide is one of the most important failure modes. In order to analyze this failure mechanism and the ease of implementation of a monitoring circuit, the gate leakage current of IGBTs was selected as the fault precursor parameter for the degradation of their gate oxide performance, and feature selection and fusion were carried out by using time domain characteristic analysis, grayscale correlation, Mahalanobis distance, Kalman filter, and other methods.

Avionics Module Fault Diagnosis Algorithm Based on Hybrid Attention Adaptive Multi-Scale Temporal Convolution Network.

Since the reliability of the avionics module is crucial for aircraft safety, the fault diagnosis and health management of this module are particularly significant. While deep learning-based prognostics and health management (PHM) methods exhibit highly accurate fault diagnosis, they have disadvantages such as inefficient data feature extraction and insufficient generalization capability, as well as a lack of avionics module fault data. Consequently, this study first employs fault injection to simulate various fault types of the avionics module and performs data enhancement to construct the P2020 communications processor fault dataset.

CT and MRI Medical Image Fusion Using Noise-Removal and Contrast Enhancement Scheme with Convolutional Neural Network.

Medical image fusion (MIF) has received painstaking attention due to its diverse medical applications in response to accurately diagnosing clinical images. Numerous MIF methods have been proposed to date, but the fused image suffers from poor contrast, non-uniform illumination, noise presence, and improper fusion strategies, resulting in an inadequate sparse representation of significant features. This paper proposes the morphological preprocessing method to address the non-uniform illumination and noise by the bottom-hat-top-hat strategy.