MOTIVATION: Integrating the knockoff framework with any variable-selection method delivers stringent false discovery rate (FDR) control without recourse to p-values, offering a powerful alternative for differential expression analysis of high-throughput omics datasets. However, existing knockoff generators rely on restrictive modelling assumptions or coarse approximations that often inflate the FDR when applied to real-world data. RESULTS: We introduce Partial Least Squares Knockoff (PLSKO), an efficient, assumption-free generator that remains robust across diverse omics platforms. Our extensive simulations show that PLSKO is the only method to maintain FDR control with sufficient power in complex non-linear settings. Our semi-simulation studies drawn from RNA-seq, proteomics, metabolomics, and microbiome experiments confirm PLSKO generates valid knockoff variables. In pre-eclampsia multi-omics case studies, we combine PLSKO with Aggregation Knockoff to address the randomness of knockoffs and improve power, and demonstrate the method's ability to recover biologically meaningful features. AVAILABILITY AND IMPLEMENTATION: Our proposed algorithm is available on Github (https://github.com/guannan-yang/PLSKO) and Zenodo (https://doi.org/10.5281/zenodo.16879594).

In the cloud storage applications, the cloud service provider (CSP) may delete or damage the user’s data. In order to avoid the responsibility, CSP will not actively inform the users after the data damage, which brings the loss to the user. Therefore, increasing research focuses on the public auditing technology recently. However, most of the current auditing schemes rely on the trusted third public auditor (TPA). Although the TPA brings the advantages of fairness and efficiency, it cannot get rid of the possibility of malicious auditors, because there is no fully trusted third party in the real world. As an emerging technology, blockchain technology can effectively solve the trust problem among multiple individuals, which is suitable to solve the security bottleneck in the TPA-based public auditing scheme. This paper proposed a public auditing scheme with the blockchain technology to resist the malicious auditors. In addition, through the experimental analysis, we demonstrate that our scheme is feasible and efficient.

Space communications are characterized by link intermittent connectivity and long link propagation delay. The use of bundle protocol (BP) in space communications has been in debate. An analytical understanding of its performance for reliable data delivery in the presence of link intermittent connectivity, especially with a lengthy link disruption, is quickly needed. In this paper, analytical models are built to estimate the number of transmission rounds (or efforts) caused by the link disruption and the resulting delay in bundle delivery of BP for applications in space communication networks. The models are validated by conducting bundle delivery experiments using a testbed.

Game theory has made great contributions to Cognitive Radio (CR) algorithm design and it calls up wide interest of CR researchers, while the considerable iterations and the operation complexity would hinder its implementation. And the evaluation under practical environment is an indispensable step before its application. To alleviate the concerns, we propose a distributed relay selection algorithm based on Stackelberg Game and overcome the challenges caused by the high calculation complexity to make our strategy applicable. Moreover, we utilize a real time testbed to evaluate the CR MAC algorithm, which contains the necessary components: programmable RF layer, software-defined MAC layer and adaptive network layer to fulfill the requirements of CR research. It is based on system-on-chip processors with strong configure ability which can develop large scale network. We make experiments on our platform to reveal the game equilibrium's properties and verify our scheme's performance in improving the capacity at the destination and secondary user's spectrum utilization efficiency.