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Prior to the identification of low pathogenic avian influenza H9N2 viruses belonging to the Y280 lineage in 2020, Y439 lineage viruses had been circulating in the Republic of Korea since 1996. Here, we developed a whole inactivated vaccine (vac564) by multiple passage of Y439 lineage viruses and then evaluated immunogenicity and protective efficacy in specific-pathogen-free chickens. We found that LBM564 could be produced at high yield in eggs (108.4EID50/0.1 mL; 1024 hemagglutinin units) and was immunogenic (8.0 ± 1.2 log2) in chickens. The vaccine showed 100% inhibition of virus in the cecal tonsil with no viral shedding detected in either oropharyngeal or cloacal swabs after challenge with homologous virus. However, it did not induce effective protection against challenge with heterologous virus. An imported commercial G1 lineage vaccine inhibited viral replication against Y280 and Y439 lineage viruses in major tissues, although viral shedding in oropharyngeal and cloacal swabs was observed up until 5 dpi after exposure to both challenge viruses. These results suggest that a single vaccination with vac564 could elicit immune responses, showing it to be capable of protecting chickens against the Y439 lineage virus. Thus, our results suggest the need to prepare suitable vaccines for use against newly emerging and re-emerging H9N2 viruses.

As the world becomes increasingly data-centric, the tasks dealt with by a database management system (DBMS) become more complex and diverse. Compared with traditional workloads that typically require only a single data model, modern-day computational tasks often involve multiple data sources and rely on more than one data model. Unfortunately, however, there is currently no standard benchmark program that can evaluate a DBMS in the various aspects of multi-model databases, especially when the array data model is concerned. In this paper, we propose M2Bench , a new benchmark program capable of evaluating a multi-model DBMS that supports several important data models such as relational, document-oriented, property graph, and array models. M2Bench consists of multi-model workloads that are inspired by real-world problems. Each task of the workload mimics a real-life scenario where at least two different models of data are involved. To demonstrate the efficacy of M2Bench , we evaluated polyglot or multi-model database systems with the M2Bench workloads and unfolded the diverse characteristics of the database systems for each data model.

Researchers su er from two problems while building a data processing pipeline for atmospheric scanning LiDAR. First, they must build an entire system that handles collecting signals, processing data, and visualizing the results. Second, they should support fast data processing to expand and deploy their system. In this paper, we introduce MISE, a fast integrated system that handles atmospheric scanning LiDAR data. MISE provides end-to-end processing, conguration options, and prede ned signal-processing methods. In addition, the system uses an e cient chunking approach for fast processing with an array database. We demonstrate the construction and operation of a ne-dust particle monitoring system (based on a real-world scenario) using MISE. This demonstration demonstrates the usability and fast performance of MISE. CCS CONCEPTS• Information systems → Information systems applications; Database design and models.