To select suitable supplier for complex equipment military-civilian collaborative design based on fuzzy preference information that from matching perspective

Combine complex equipment collaborative development in military-civilian integration context not only fulfils actual development requirement, but also beneficial to the national economy. Design procedure as first stage of complex equipment military-civilian collaborative development process, select suitable design supplier is significant to whole development process of complex equipment. In order to select suitable design supplier for complex equipment, two aspects done in this paper. One is comprehensive analysis of evaluated influencing factors that affect complex equipment military-civilian collaborative design process, corresponding evaluation indicator constructed and a combination of grey correlation, entropy, DEMATEL (Decision-making Trial and Evaluation Laboratory) and VIKOR analysis theory to obtain grey entropy-DEMATEL-VIKOR, then the combined method is utilized to acquire matching attributes for followed research content. Meanwhile, satisfaction degree for matching side obtained with the help of information aggregation based on power generalized Heronian mean which on the basis of fuzzy preference information. Then, through constructed matching model, suitable design supplier obtained. Finally, a corresponding illustrative example given.

A collaboratively-derived research agenda for e-assessment in university mathematics

This paper describes the collaborative development of an agenda for research on e-assessment in university mathematics. We adapted an established approach to develop the agenda from the contributions of 22 mathematics education researchers, university teachers and learning technologists interested in this topic. The resulting set of 55 questions are grouped into 5 broad themes: errors and feedback, students, design and implementation, affordances, and mathematical skills. This agenda gives the framework for a programme of research aligned with practical concerns, that will contribute to both theoretical and practical development.

Advancing data science in drug development through an innovative computational framework for data sharing and statistical analysis

Background Novartis and the University of Oxford’s Big Data Institute (BDI) have established a research alliance with the aim to improve health care and drug development by making it more efficient and targeted. Using a combination of the latest statistical machine learning technology with an innovative IT platform developed to manage large volumes of anonymised data from numerous data sources and types we plan to identify novel patterns with clinical relevance which cannot be detected by humans alone to identify phenotypes and early predictors of patient disease activity and progression. Method The collaboration focuses on highly complex autoimmune diseases and develops a computational framework to assemble a research-ready dataset across numerous modalities. For the Multiple Sclerosis (MS) project, the collaboration has anonymised and integrated phase II to phase IV clinical and imaging trial data from ≈35,000 patients across all clinical phenotypes and collected in more than 2200 centres worldwide. For the “IL-17” project, the collaboration has anonymised and integrated clinical and imaging data from over 30 phase II and III Cosentyx clinical trials including more than 15,000 patients, suffering from four autoimmune disorders (Psoriasis, Axial Spondyloarthritis, Psoriatic arthritis (PsA) and Rheumatoid arthritis (RA)). Results A fundamental component of successful data analysis and the collaborative development of novel machine learning methods on these rich data sets has been the construction of a research informatics framework that can capture the data at regular intervals where images could be anonymised and integrated with the de-identified clinical data, quality controlled and compiled into a research-ready relational database which would then be available to multi-disciplinary analysts. The collaborative development from a group of software developers, data wranglers, statisticians, clinicians, and domain scientists across both organisations has been key. This framework is innovative, as it facilitates collaborative data management and makes a complicated clinical trial data set from a pharmaceutical company available to academic researchers who become associated with the project. Conclusions An informatics framework has been developed to capture clinical trial data into a pipeline of anonymisation, quality control, data exploration, and subsequent integration into a database. Establishing this framework has been integral to the development of analytical tools.

Practices and thinking of public libraries in China during COVID-19

As a result of the COVID-19 pandemic, libraries in China closed their doors in early 2020 and moved all their services online. This change has brought unprecedented challenges for the development of library services, while it has also brought opportunities and motivation for the future transformation of libraries. This article uses official WeChat accounts of the National Library of China and more than 30 provincial public libraries as the main information sources to summarize and classify the services provided during the period of closure. It also collates and analyses news items released by these libraries to guide the improvement of the online services of public libraries in the pandemic environment. Finally, it puts forward the author’s reflections and suggestions on the key development directions of libraries in the post-pandemic era in six areas: reading promotion, smart libraries, new media operation, information literacy cultivation, open access and collaborative development.

THE RESPONSIBILITIES OF THE SOCIAL MEDIA FROM INDIA AND CHINA ON THE GLOBAL PANDEMIC

The worldwide pandemics are the common enemy of all mankind.When faced with the global pandemics, it becomes necessary for all nations to strengthen cooperation.Although India and China are close neighbors in Asia,their media coverage of each other in 2020 was extremely asymmetrical.Nonetheless,this media coverage should be strengthening communication and cooperation.Only in this way can it benefit the people of the two nations and ultimately realize a coprosperity and collaborative development.