Shaohua Xu

Oct 29, 2024 | medrxiv.org | Shaohua Xu

The authors have declared no competing interest. This work was supported by Science and Technology Plan Project of Wuwei, Grant/Award Numbers :WW2202RPZ032I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. YesThe details of the IRB/oversight body that provided approval or exemption for the research described are given below:The study used ONLY openly available human data that were originally located UCSC Xena.

Aug 20, 2024 | journalofcloudcomputing.springeropen.com | Zhen Zhang |Chen Xu |Jinyu Zhang |Zhe Zhu |Shaohua Xu

To address the challenge of load prediction in cloud computing environments, researchers have proposed various methods aimed at enhancing prediction accuracy to optimize resource allocation and improve system performance. Generally, these methods fall into three categories: statistical learning, RNNs, and Transformers. In response to the highly variable cloud loads, Gupta et al. [26] proposed an online adaptive method for predicting cloud resource usage time series.

Jul 1, 2024 | onlinelibrary.wiley.com | Chenxia Guo |Shaohua Xu |Wei Yan

INTRODUCTION Acinetobacter baumannii (AB) is a gram-negative, aerobic, rod-shaped bacterium that has become an important pathogen that causes hospital-acquired infections worldwide because of its strong acquired resistance, clonal spread, and long-term survival ability in hospital environments.