E-DANN: An Enhanced Domain Adaptation Network for Audio-EEG Feature Decoupling in Explainable Depression Recognition.

Given the significant global health burden caused by depression, numerous studies have utilized artificial intelligence techniques to objectively and automatically detect depression. However, existing research primarily focuses on improving the accuracy of depression recognition while overlooking the explainability of detection models and the evaluation of feature importance. In this paper, we propose a novel framework named Enhanced Domain Adversarial Neural Network (E-DANN) for depression detection.

3D-Printed Array Helical Monolithic Column Chip with Hierarchical Porous Structure for High-Throughput ICP-MS Analysis of Trace Rare-Earth Elements.

Three-dimensional printing (3DP) technology enables the flexible fabrication of integrated monolithic microextraction chips for high-throughput sample pretreatment. Meanwhile, the extraction performance of 3DP-based channels is largely limited by printer resolution and the commercially available printing materials. In this work, a 3DP array monolithic microextraction chip (AMC) was fabricated by integrating 26-array helical monolithic microextraction channels for sample pretreatment and 52-array gas valves for fluid control.

Association of Oxidative Balance Score With All-Cause and Cardiovascular Mortality Among Hypertensive Adults.

Background: The Oxidative Balance Score (OBS) is a new measure for assessing systemic oxidative stress, where higher scores indicate increased exposure to antioxidants. However, the relationship between the OBS and mortality in individuals with hypertension remains unclear.

Methods: This study evaluated 8151 hypertensive individuals from the National Health and Nutrition Examination Survey (NHANES) (2001-2018), utilizing data from the National Death Index, tracked through December 31, 2019.

Digital image encryption utilizing high-dimensional cellular neural networks and lower-upper triangular decomposition of matrix.

At present, significant progress has been made in the research of image encryption, but there are still some issues that need to be explored in key space, password generation and security verification, encryption schemes, and other aspects. Aiming at this, a digital image encryption algorithm was developed in this paper. This algorithm integrates six-dimensional cellular neural network with generalized chaos to generate pseudo-random numbers to generate the plaintext-related ciphers.

Cerebral Venous Thrombosis:Current Status and Challenges.

Background: Cerebral venous thrombosis (CVT) is a stroke type that primarily affects young individuals, with various risk factors and complex mechanisms. It accounts for 0.5% to 3% of all stroke cases and can significantly impact daily activities and quality of life.