Hierarchical Clustering on Principal Components Analysis to Detect Clusters of Highly Pathogenic Avian Influenza Subtype H5N6 Epidemic across South Korean Poultry Farms

Evolution and Spread of Highly Pathogenic Avian Influenza A(H5N1) Clade 2.3.4.4b Virus in Wild Birds, South Korea, 2022-2023

During October 2022-March 2023, highly pathogenic avian influenza (HPAI) A(H5N1) clade 2.3.4.4b virus caused outbreaks in South Korea, including 174 cases in wild birds. To understand the origin and role of wild birds in the evolution and spread of HPAI viruses, we sequenced 113 HPAI isolates from wild birds and performed phylogenetic analysis. We identified 16 different genotypes, indicating extensive genetic reassortment with viruses in wild birds. Phylodynamic analysis showed that the viruses were most likely introduced to the southern Gyeonggi-do/northern Chungcheongnam-do area through whooper swans (Cygnus cygnus) and spread southward. Cross-species transmission occurred between various wild bird species, including waterfowl and raptors, resulting in the persistence of HPAI in wild bird populations and further geographic spread as these birds migrated throughout South Korea. Enhanced genomic surveillance was an integral part of the HPAI outbreak response, aiding in timely understanding of the origin, evolution, and spread of the virus.

Reducing waste management scenario space for developing countries: A hierarchical clustering on principal components approach

The complexity of waste management (WM) problems resulted in the explosion of scenarios that challenge focused discussion among stakeholders and hinder the integrity of policy responses in developing countries. Hence, drawing similarities is essential to reduce the number of scenarios to simplify the WM efforts. To extract similarities, measuring WM performance is not enough, but the background factors related to this performance should be incorporated. These factors form a unique system characteristic that facilitates or hinders WM functions. Thus, this study applied multivariate statistical analysis to clarify underlying characteristics that facilitate efficient WM scenario developments for developing countries. The study first analysed drivers associated with improved WM system performance using bivariate correlation analysis. As a result, twelve significant drivers associated with controlled solid waste were identified. Then, it mapped the countries based on their WM system characteristics using the combined principal component analysis and hierarchical clustering approach. Thirteen variables were examined to extract similarities between the countries. The results identified three homogenous clusters. The clusters were found considerably parallel to the global classifications based on income and human development index. Hence, the presented approach is efficient in explaining similarities that reduce WM scenarios and favours cooperation among countries.

Interpretive analysis of online teaching labs constructed using moodle during the pandemic period

The Algerian Ministry of Higher Education announced the closure of universities and switched to distance teaching due to the strong and rapid spread of COVID-19. The pandemic that forced this change created many obstacles to pedagogy. In fact, many related issues had to be resolved and other alternative teaching strategies examined. This article defines a strategy that ensures the pedagogical continuity of laboratory practical work of computer graphics course in a COVID- 19 context. It also includes data analysis of student satisfaction questionnaire on the lab work strategy quality. As a result of this research, the success rates in the graphics design course reached 91,79% and students' grades ranged from 4.33/20 to 18.17/20. This result is consistent with the combined-type graphical representation of COLLES. Guidelines and best practices are provided for performing online learning labs, including the university's online learning platform as well as different teaching scenarios, tutoring and peer assessment techniques. Computer science instructors can use this innovative strategy to develop content-specific courses, establish recommended skills, and deploy technology to improve their teaching methods.