Integration tools for scRNA-seq data and spatial transcriptomics sequencing data.

Numerous methods have been developed to integrate spatial transcriptomics sequencing data with single-cell RNA sequencing (scRNA-seq) data. Continuous development and improvement of these methods offer multiple options for integrating and analyzing scRNA-seq and spatial transcriptomics data based on diverse research inquiries. However, each method has its own advantages, limitations and scope of application.

Online data poisoning attack against edge AI paradigm for IoT-enabled smart city.

The deep integration of edge computing and Artificial Intelligence (AI) in IoT (Internet of Things)-enabled smart cities has given rise to new edge AI paradigms that are more vulnerable to attacks such as data and model poisoning and evasion of attacks. This work proposes an online poisoning attack framework based on the edge AI environment of IoT-enabled smart cities, which takes into account the limited storage space and proposes a rehearsal-based buffer mechanism to manipulate the model by incrementally polluting the sample data stream that arrives at the appropriately sized cache. A maximum-gradient-based sample selection strategy is presented, which converts the operation of traversing historical sample gradients into an online iterative computation method to overcome the problem of periodic overwriting of the sample data cache after training.

Research on Data Poisoning Attack against Smart Grid Cyber-Physical System Based on Edge Computing.

Data poisoning attack is a well-known attack against machine learning models, where malicious attackers contaminate the training data to manipulate critical models and predictive outcomes by masquerading as terminal devices. As this type of attack can be fatal to the operation of a smart grid, addressing data poisoning is of utmost importance. However, this attack requires solving an expensive two-level optimization problem, which can be challenging to implement in resource-constrained edge environments of the smart grid.

Single-Cell Sequencing Reveals Differential Cell Types in Skin Tissues of Liaoning Cashmere Goats and Key Genes Related Potentially to the Fineness of Cashmere Fiber.

Cashmere fineness is one of the important factors determining cashmere quality; however, our understanding of the regulation of cashmere fineness at the cellular level is limited. Here, we used single-cell RNA sequencing and computational models to identify 13 skin cell types in Liaoning cashmere goats. We also analyzed the molecular changes in the development process by cell trajectory analysis and revealed the maturation process in the gene expression profile in Liaoning cashmere goats.