Key issues in the implementation of the Tianjin Biosecurity Guidelines for codes of conduct for scientists: a survey of biosecurity education projects

In order to effectively implement the Tianjin Biosecurity Guidelines in codes of conduct for life scientists, biosecurity awareness-raising and education are essential because if these are not in place scientists will not understand the need for biosecurity codes of conduct. In an effort to assist in the consideration of the implementation of the guidelines a small-scale survey was carried out in early 2022 of biosecurity awareness-raising and education projects that have been developed over the last two decades with a view to discovering what resources and experience has been accumulated. It is argued that the survey demonstrates that much of what is needed to effectively implement the guidelines has been developed, but that there are specific deficiencies that need to be remedied quickly. In particular, an updated teaching resource covering the core issues related to the Biological and Toxin Weapons Convention (BTWC) and the problem of dual use in scientific research needs to be made widely available and translated into at least the six official UN languages. Additionally, more specialists from the Humanities with expertise in ethics need to become involved in biosecurity awareness-raising and education activities, and while advantage should be taken now of the available national, regional and international networks of people involved in related activities, it is suggested that in the longer term cooperation in biosecurity awareness-raising and education will benefit from the development of an equivalent organisation to the International Nuclear Security Education Network (INSEN) organised through the IAEA

Data ingestion pipeline and data marts to empower UK researchers, academics, and business and economic decision makers

The data integration problem from the voluminous data generated from different sources in disparate formats coupled with a large number of diverse requirements related to the data have made the need for a reconciliation of them into a unique model, the identification of relationships, and the enabling of data analytics processes extremely vital. In light of the unabated growth of data volume and the need for data sharing across various stakeholders there is a requirement for the design and implementation of a data ingestion pipeline with a set of data marts. In this paper, we present a data ingestion pipeline which empowers hitherto impeded data users to easily access shared big data sources. We aim to improve the effectiveness and efficiency of open 993source data sharing capability so that researchers, academics, policy makers, businesses and government departments can all benefit from the use of these sophisticated data management techniques. In this work, we propose a novel data ingestion pipeline and data marts approach to utilise data generated from big data systems and effectively integrate them to a unified form, ready for use. Currently, the data ingestion pipeline focuses on UK data, as our primary aim is to support the City of London and the various communities within it. An additional benefit is the potential for developing collaboration across disciplines to tackle the economic and social challenges faced by cities in innovative ways

Retention of computing students in a London-based university during the Covid-19 pandemic using learned optimism as a lens: a statistical analysis in R

The aim of this research project is to investigate the low retention rate among the foundation and first year undergraduate students from the School of Computing and Digital Media in a London based university. Specifically, the research is conducted during the Covid-19 pandemic using learned optimism as a lens. The research will aid the university to improve retention rate as the overall dropout has been increasing in the last few years. The current study employed an exploratory investigation approach by using statistical modelling analysis in R to predict behavioural patterns. The quantitative data analysis conducted aims to support the efforts of the School of Computing and Digital Media of a London based university to re-evaluate its retention strategies in foundation and first year computing students. The main outcomes of the analysis is that students with a foreign qualification are optimistic, while students with other or not known qualification are mildly pessimistic. In addition, students with a BTECH, Higher Education diploma or A level qualification are generally more pessimistic especially if they are also black ethnicity, or are also not black ethnicity, aged under 34 and British