Artificial Intelligence

This dataset, constructed around the Jilin Baishan Incident, aims to enhance the emotion prediction capabilities of large language models. Approximately 3.5 million raw comments were collected via the Weibo API, covering key information such as user identifiers, text content, timestamps, and interaction metrics. The data underwent preprocessing steps including normalization, Chinese tokenization, stopword removal, deduplication, and anomalous sample exclusion.

The data is derived from 22,898 comments on driverless and human driving obtained by crawler technology on China's Weibo and XiaoHongshu platforms from May 1 to August 31, 2024. The main data formats are xlsx, py, txt, json and so on. The files in py format are script files, which are used to process data. The dataset was eventually used for topic mining, sentiment analysis, and more on Chinese users' comments on driverless and human driving.

miRNAs influence cellular functions by regulating gene expression and interacting with diverse biomolecules within the cell. Accurate prediction of miRNAdisease associations (MDA) plays a crucial role in disease diagnosis, treatment, and drug development. However, existing computational methods focus on network structure and ignore multi-view information such as linear and non-linear when extracting miRNA and disease features. In addition, these models are generally “blackbox” in nature, which limits the understanding of their prediction mechanisms.

Shape completion remains a fundamental challenge in computer vision and image processing, particularly for tasks involving hand-drawn sketches and occluded objects. Traditional deep learning methods such as Generative Adversarial Networks (GANs) and Convolutional Neural Networks (CNNs) often suffer from high computational costs and poor generalization on sparse, abstract structures.