DualStreamFoveaNet: A Dual Stream Fusion Architecture with Anatomical Awareness for Robust Fovea Localization.

Accurate fovea localization is essential for analyzing retinal diseases to prevent irreversible vision loss. While current deep learning-based methods outperform traditional ones, they still face challenges such as the lack of local anatomical landmarks around the fovea, the inability to robustly handle diseased retinal images, and the variations in image conditions. In this paper, we propose a novel transformer-based architecture called DualStreamFoveaNet (DSFN) for multi-cue fusion.

Identification and exploration of aging-related subtypes and distinctive role of SERPINE1 in heart failure based on single-cell and bulk RNA sequencing data.

Aging is a major risk factor for heart failure (HF) and is the leading cause of death worldwide. Currently, the nature of the relationship between aging and HF is not entirely clear. Herein, this study aimed to explore new diagnostic biomarkers, molecular typing and therapeutic strategies for HF by investigating the biological significance of aging-related genes in HF.

Integrating scRNA-seq to explore novel macrophage infiltration-associated biomarkers for diagnosis of heart failure.

Objective: Inflammation and immune cells are closely intertwined mechanisms that contribute to the progression of heart failure (HF). Nonetheless, there is a paucity of information regarding the distinct features of dysregulated immune cells and efficient diagnostic biomarkers linked with HF. This study aims to explore diagnostic biomarkers related to immune cells in HF to gain new insights into the underlying molecular mechanisms of HF and to provide novel perspectives for the detection and treatment of HF.

GAMMA challenge: Glaucoma grAding from Multi-Modality imAges.

Glaucoma is a chronic neuro-degenerative condition that is one of the world's leading causes of irreversible but preventable blindness. The blindness is generally caused by the lack of timely detection and treatment. Early screening is thus essential for early treatment to preserve vision and maintain life quality.

From deterministic to stochastic: an interpretable stochastic model-free reinforcement learning framework for portfolio optimization.

As a fundamental problem in algorithmic trading, portfolio optimization aims to maximize the cumulative return by continuously investing in various financial derivatives within a given time period. Recent years have witnessed the transformation from traditional machine learning trading algorithms to reinforcement learning algorithms due to their superior nature of sequential decision making. However, the exponential growth of the imperfect and noisy financial data that is supposedly leveraged by the deterministic strategy in reinforcement learning, makes it increasingly challenging for one to continuously obtain a profitable portfolio.

RC-Net: Regression Correction for End-To-End Chromosome Instance Segmentation.

Precise segmentation of chromosome in the real image achieved by a microscope is significant for karyotype analysis. The segmentation of image is usually achieved by a pixel-level classification task, which considers different instances as different classes. Many instance segmentation methods predict the Intersection over Union (IoU) through the head branch to correct the classification confidence.

FECTS: A Facial Emotion Cognition and Training System for Chinese Children with Autism Spectrum Disorder.

Traditional training methods such as card teaching, assistive technologies (e.g., augmented reality/virtual reality games and smartphone apps), DVDs, human-computer interactions, and human-robot interactions are widely applied in autistic rehabilitation training in recent years.

Effects of chronic intermittent hypoxia on left cardiac function in young and aged mice.

Obstructive sleep apnea (OSA) is an independent risk factor for cardiovascular disease that is characterized by chronic intermittent hypoxia (CIH), and its impact is related to age. This study aims to assess the age-related impact of CIH on cardiac function and to further explore the mechanism. After 8 wk of severe CIH exposure, the hearts of young mice showed slight physiological hypertrophy, decreased diastolic function, and collagen I accumulation but no obvious change in contractile function.

Intention Understanding in Human-Robot Interaction Based on Visual-NLP Semantics.

With the rapid development of robotic and AI technology in recent years, human-robot interaction has made great advancement, making practical social impact. Verbal commands are one of the most direct and frequently used means for human-robot interaction. Currently, such technology can enable robots to execute pre-defined tasks based on simple and direct and explicit language instructions, e.