Accurate gene regulatory network (GRN) inference from single-cell RNA sequencing (scRNA-seq) data is challenged by high sparsity, noise, and confounders, causing confounding bias and ambiguous directions in traditional methods. To overcome this, we propose the Counterfactual Causality-aware Framework for Gene Regulatory Networks (CfCGRN). Building on counterfactual intervention, CfCGRN employs Conditional Variational Autoencoders (CVAEs) to generate perturbation-mimicking counterfactual samples. It incorporates a confounder-aware graph attention layer with learnable backdoor adjustments to explicitly eliminate confounding bias. An expression gradient-guided attention mask enforces directional information flow from highly to lowly expressed genes, enabling directed causal inference. Evaluations on DREAM5 and diverse scRNA-seq datasets demonstrate CfCGRN's significant improvements in GRN inference accuracy, directionality discrimination, and biological interpretability, offering a novel tool for deciphering key regulatory pathways.

Recent years have witnessed a rapid growth of both 5G coverage and 5G users, attracting several measurement studies on its coverage, reliability and quality of service. However, the capabilities and potential impacts of 5G, especially Standalone (SA) 5G, still remain to be fully understood from a content provider (CP)’s perspective. This paper fills this gap by studying 5G networks used by over 23 million users in one year in Kuaishou, a popular crowdsourced live streaming platform. With passive and active measurements, we have the following key findings: i) SA 5G generally provides end-to-end performance improvements compared to 4G or Non-Standalone (NSA) 5G, but its advantage depends on both the number of cellular users and CP-level configurations. ii) In the radio access networks, SA 5G is more sensitive to access density, but has better handover tolerance. iii) Controlled experiments with 29 mobile device models on energy consumption refute some “conventional wisdom,” including the notion that 5G always consumes more power. iv) Traceroute-based active experiments in over 300 cities show that although users are “closer” to the internet in SA 5G due to the control and user plane separation, whether end-to-end latency benefits from that partly depends on the routing policy at the gateways. Furthermore, we propose a 5G-aware rebuffer strategy tested by 9 million viewers in Kuaishou, showing a 7% reduction in rebuffer proportion. Finally, we also provide new design space for other 5G participants.

5G has seen rapid growth recently, attracting several measurement studies on its coverage, connectivity and quality of service. However, there is still a lack of understanding of 5G's capabilities and potential impacts from a content provider (CP)'s perspective. This paper fills in this gap by studying 5G networks used by over 23 million users in one year in Kuaishou, a popular crowdsourced live streaming platform. Our measurements provide the following discoveries. i) Standalone (SA) 5G generally provides end-to-end performance improvement as compared with 4G or non-SA (NSA) 5G, but its advantage depends on both the number of cellular users and CP-level configurations. ii) In the radio access network, SA 5G is more sensitive to access density but has better handover tolerance. iii) Controlled experiments with 29 mobile device models on energy consumption refute some "conventional wisdom," including that 5G always consumes more power. iv) Traceroute-based active experiments in over 300 cities show that although users are "closer" to the internet in SA 5G, their end-to-end latency may not benefit from that. Furthermore, we show new design space for 5G participants and provide a 5G-aware rebuffer strategy tested by 9 million viewers in Kuaishou, with a 7% reduction in rebuffer proportion.