Efficient Masked Autoencoders With Self-Consistency.

Inspired by the masked language modeling (MLM) in natural language processing tasks, the masked image modeling (MIM) has been recognized as a strong self-supervised pre-training method in computer vision. However, the high random mask ratio of MIM results in two serious problems: 1) the inadequate data utilization of images within each iteration brings prolonged pre-training, and 2) the high inconsistency of predictions results in unreliable generations, i.e.

Advancements in the study of synaptic plasticity and mitochondrial autophagy relationship.

Synapses serve as the points of communication between neurons, consisting primarily of three components: the presynaptic membrane, synaptic cleft, and postsynaptic membrane. They transmit signals through the release and reception of neurotransmitters. Synaptic plasticity, the ability of synapses to undergo structural and functional changes, is influenced by proteins such as growth-associated proteins, synaptic vesicle proteins, postsynaptic density proteins, and neurotrophic growth factors.

Effects of Dihuang Yinzi Decoction on Alzheimer's Disease: A Systematic Review and Meta-Analysis.

Objective: The aim of this study was to systematically evaluate the therapeutic effects of Dihuang Yinzi decoction on Alzheimer's disease (AD) and provide a medical evidence-based clinical application of traditional Chinese medicine (TCM).

Methods: A comprehensive search was conducted across multiple databases, including PubMed, Embase, Cochrane Library, China National Journals Full-text Database, VIP Database for Chinese Technical Periodicals, Wan Fang database, and SinoMed database, to collect clinical randomized controlled trials of Dihuang Yinzi decoction in the treatment of AD. Strict literature screening was performed based on predefined inclusion and exclusion criteria.

Attention CoupleNet: Fully Convolutional Attention Coupling Network for Object Detection.

The field of object detection has made great progress in recent years. Most of these improvements are derived from using a more sophisticated convolutional neural network. However, in the case of humans, the attention mechanism, global structure information, and local details of objects all play an important role for detecting an object.