Creating partnerships for capacity building in developing countries - the experience of the World Bank

The authors discuss a variety of experiences in a number of transition, and developing countries to build institutional capacity for economics education. A flexible approach met with some success. The approach uses partnerships that combine the often different needs of a number of private donors, with the World Bank on the supply side. Much of the success was due to adopting each effort to the individual country situation. The authors also provide a brief summary of five academic institutions, and four research networks in Europe, Africa, Asia, and Latin America.Public Health Promotion,Health Monitoring&Evaluation,Agricultural Knowledge&Information Systems,Decentralization,ICT Policy and Strategies,ICT Policy and Strategies,Health Monitoring&Evaluation,Agricultural Knowledge&Information Systems,Tertiary Education,Scientific Research&Science Parks

Factors facilitating sustainable scientific partnerships between developed and developing countries

International scientific partnerships are key to the success of strategic investments in plant science research and the farm-level adoption of new varieties and technologies, as well as the coherence of agricultural policies across borders to address global challenges. Such partnerships result not only in a greater impact of published research enhancing the career development of early and later stage researchers, but they also ensure that advances in plant science and crop breeding technologies make a meaningful contribution to society by brokering acceptance of emerging solutions to the world problems. We discuss the evidence showing that despite a lack of funding, scientists in some African countries make a significant contribution to global science output. We consider the criteria for success in establishing long-term scientific partnerships between scientists in developing countries in Southern Africa (“the South”) and developed countries such as the UK (“the North”). We provide our own personal perspectives on the key attributes that lead to successful institutional collaborations and the establishment of sustainable networks of successful “North-South” scientific partnerships. In addition, we highlight some of the stumbling blocks which tend to hinder the sustainability of long-term “North-South” scientific networks. We use this personal knowledge and experiences to provide guidelines on how to establish and maintain successful long-term “North-South” scientific partnerships.National Research Foundation of South Africa, Winter Cereal Trust and African Union Research Grant Programme funded by the European Union.http://journals.sagepub.com/home/oaghj2021Forestry and Agricultural Biotechnology Institute (FABI)Plant Production and Soil Scienc

Management of Scientific Experiments in Computational Modeling: Challenges and Perspectives

Currently the computer is essential to the success in conducting scientific research. In this context, e-Science appears as science performed with computer support aiming efficiency. The challenge, “Computational Modeling of artificial, naturals and socio-cultural complex systems and man-nature interaction” from SBC Great Challenges is strongly related to the e-Science context. The goal of this challenge is to create, evaluate, modify, compose, manage and exploit computer models in fields related to complex, artificial, natural, socio-cultural and human-nature systems. Technologies like semantic web service composition, data provenance, peer to peer networks and scientific software product line can be used as basis for the specification and development of an e-Science infrastructure to handle challenges and solve problems. This paper discusses the main challenges involved in developing an eScience infrastructure, presenting research challenges for the next years

Interests Diffusion in Social Networks

Understanding cultural phenomena on Social Networks (SNs) and exploiting the implicit knowledge about their members is attracting the interest of different research communities both from the academic and the business side. The community of complexity science is devoting significant efforts to define laws, models, and theories, which, based on acquired knowledge, are able to predict future observations (e.g. success of a product). In the mean time, the semantic web community aims at engineering a new generation of advanced services by defining constructs, models and methods, adding a semantic layer to SNs. In this context, a leapfrog is expected to come from a hybrid approach merging the disciplines above. Along this line, this work focuses on the propagation of individual interests in social networks. The proposed framework consists of the following main components: a method to gather information about the members of the social networks; methods to perform some semantic analysis of the Domain of Interest; a procedure to infer members' interests; and an interests evolution theory to predict how the interests propagate in the network. As a result, one achieves an analytic tool to measure individual features, such as members' susceptibilities and authorities. Although the approach applies to any type of social network, here it is has been tested against the computer science research community. The DBLP (Digital Bibliography and Library Project) database has been elected as test-case since it provides the most comprehensive list of scientific production in this field.Comment: 30 pages 13 figs 4 table

Assessment of gender divide in scientific communities

AbstractIncreasing evidence of women's under-representation in some scientific disciplines is prompting researchers to expand our understanding of this social phenomenon. Moreover, any countermeasures proposed to eliminate this under-representation should be tailored to the actual reasons for this different participation. Here, we take a multi-dimensional approach to assessing gender differences in science by representing scientific communities as social networks, and using data analytics, complexity science methods, and semantic methods to measure gender differences in the context, the attitude and the success of scientists. We apply this approach to four scientific communities in the two fields of computer science and information systems using the network of authors at four different conferences. For each discipline, one conference is based in Italy and attracts mostly Italians, while one conference is international in both location and participants. The present paper provides evidence against common narratives that women's under-representation is due to women's limited skills and/or less social centrality

Predicting of a person's life activity through quantitative indicators of her personal profile in social networks (on the example of predicting the academic success of students)

The object of this paper is to identify psychological patterns of academic success of an individual as a manifestation of his life activity, based on the analysis of quantitative indicators (metrics) of his profile in social networks. The leading method of research was an ascertaining experiment that included diagnostics of students’ academic success (N≈30 000) and components of their personal profile in social networks (psychometrics). The article shows the features of interaction between real and virtual activity of students through quantitative indicators of their personal profile metrics in social networks. The presented materials significantly fill the psychology of social networks (a new field of psychology, which is at the initial stage of its forming) with knowledge about the psychological regularities of the correlation of academic success of a person with the characteristics of her virtual activity in social networks. The project is implemented within the framework of intensive development of digital technologies and their deep integration into the social space. The results of the study expand the possibilities for diagnosing, analysing, understanding, and predicting the behaviour of a person's success through cyberspace on the example of their academic performance. The scientific novelty of this research consists in the identification of cognitive-behavioural predictors of educational activity of an individual, which are represented in virtual reality, as the result of his activity in social networks through quantitative psychometric indicators - metrics of his personal profile in social networks.The study (all theoretical and empirical tasks of the research presented in this paper, except for the payment of publishing services) was supported by a grant from the Russian Science Foundation (Project No. 19-18-00253, «Neural network psychometric model of cognitive-behavioural predictors of life activity of a person on the basis of social networks»)

Space data management at the NSSDC (National Space Sciences Data Center): Applications for data compression

The National Space Science Data Center (NSSDC), established in 1966, is the largest archive for processed data from NASA's space and Earth science missions. The NSSDC manages over 120,000 data tapes with over 4,000 data sets. The size of the digital archive is approximately 6,000 gigabytes with all of this data in its original uncompressed form. By 1995 the NSSDC digital archive is expected to more than quadruple in size reaching over 28,000 gigabytes. The NSSDC digital archive is expected to more than quadruple in size reaching over 28,000 gigabytes. The NSSDC is beginning several thrusts allowing it to better serve the scientific community and keep up with managing the ever increasing volumes of data. These thrusts involve managing larger and larger amounts of information and data online, employing mass storage techniques, and the use of low rate communications networks to move requested data to remote sites in the United States, Europe and Canada. The success of these thrusts, combined with the tremendous volume of data expected to be archived at the NSSDC, clearly indicates that innovative storage and data management solutions must be sought and implemented. Although not presently used, data compression techniques may be a very important tool for managing a large fraction or all of the NSSDC archive in the future. Some future applications would consist of compressing online data in order to have more data readily available, compress requested data that must be moved over low rate ground networks, and compress all the digital data in the NSSDC archive for a cost effective backup that would be used only in the event of a disaster

Observations on Short-Term and Long-Range Plans for Technology Transfer to State and Local Governments

Efforts to apply the scientific and technical resources of the hundreds of Federal laboratories to the solving of technical problems of industry, State and local governments have met with only limited success. In part, this is because of lack of understanding of how to bridge the gap between highly sophisticated sources of technical information and users less skilled in technical pursuits. The National Science Foundation, in cooperation with many of the major public interest groups, has been initiating and evaluating a number of networks to bridge the gap. It has also worked with State and local governments to improve their capabilities to define clearly their technical needs and seek solutions