Centres of excellence in conservation agriculture: developing African institutions for sustainable agricultural development.

Conservation Agriculture (CA) is an important component in addressing food insecurity, biodiversity degradation and water scarcity challenges. Its adoption in Africa has lagged behind other continents. One major area of need to enable the acceleration of the adoption of CA in Africa relates to building the necessary cross-sectoral institutional and human capacity across the education-research-extension-enterprise axis along the value chain. This study was conducted in order to contribute to the discussions about the need to create sustainable institutions: specifically, Conservation Agriculture Centres of Excellence (CA-CoEs) in Africa. The CA-CoEs model includes a stakeholder team, a shared facility or an entity that provides leadership, best practices, research, support and/or training in CA, with linkages to service providers along the value chain. This literature-based research involved systematic identification, collection, analysis and documentation of data to identify and address the unique roles these CA-CoEs play in the promotion and adoption of CA and their level of performance. It employed a CA quality assurance self-assessment tool to measure the performance of the CA-CoEs against predetermined performance descriptors. Although the CA-CoEs are facilitating and catalysing adoption of CA, their capacity in providing the CA-related programmes, training and research is not optimal. CA-CoE quality assurance of services can be helpful in identification and design of measures for addressing the challenges faced. To be impactful, CA-CoEs need well-coordinated, participatory and demand-driven CA-based agricultural practices, information services and knowledge for farmers and other stakeholders such as non-governmental organizations (NGOs), CA service providers and CA equipment manufacturers.

High-volume revision surgeons have better outcomes following revision total knee arthroplasty

Aims It has previously been shown that higher-volume hospitals have better outcomes following revision total knee arthroplasty (rTKA). We were unable to identify any studies which investigated the effect of surgeon volume on the outcome of rTKA. We sought to investigate whether patients of high-volume (HV) rTKA surgeons have better outcomes following this procedure compared with those of low-volume (LV) surgeons. Methods This retrospective study involved patients who underwent aseptic unilateral rTKA between January 2016 and March 2019, using the database of a large urban academic medical centre. Surgeons who performed ≥ 19 aseptic rTKAs per year during the study period were considered HV and those who performed < 19 per year were considered LV. Demographic characteristics, surgical factors, and postoperative outcomes were compared between the two groups. Results A total of 308 rTKAs were identified, 132 performed by HV surgeons and 176 by 22 LV surgeons. The LV group had a significantly greater proportion of non-smokers (59.8% vs 49.2%; p = 0.029). For all types of revision, HV surgeons had significantly shorter mean operating times by 17.75 minutes (p = 0.007). For the 169 full revisions (85 HV, 84 LV), HV surgeons had significantly shorter operating times (131.12 (SD 33.78) vs 171.65 (SD 49.88) minutes; p < 0.001), significantly lower re-revision rates (7.1% vs 19.0%; p = 0.023) and significantly fewer re-revisions (0.07 (SD 0.26) vs 0.29 (SD 0.74); p = 0.017). Conclusion Patients of HV rTKA surgeons have better outcomes following full rTKA. These findings support the development of revision teams within arthroplasty centres of excellence to offer patients the best possible outcomes following rTKA. Cite this article: Bone Joint J 2021;103-B(6 Supple A):131–136.

Correction to: Understanding the key processes of excellence as a prerequisite to establishing academic centres of excellence in Africa

An amendment to this paper has been published and can be accessed via the original article.

Understanding the key processes of excellence as a prerequisite to establishing academic centres of excellence in Africa

Background Africa’s economic transformation relies on a radical transformation of its higher education institutions. The establishment of regional higher education Centres of Excellence (CoE) across Africa through a World Bank support aims to stimulate the needed transformation in education and research. However, excellence is a vague, and often indiscriminately used concept in academic circles. More importantly, the manner in which aspiring institutions can achieve academic excellence is described inadequately. The main objective of this paper is to describe the core processes of excellence as a prerequisite to establishing academic CoE in Africa. Methods The paper relies on our collaborative discussions and real-world insight into the pursuit of academic excellence, a narrative review using Pubmed search for a contextual understanding of CoEs in Africa supplemented by a Google search for definitions of CoEs in academic contexts. Results We identified three key, synergistic processes of excellence central to institutionalizing academic CoEs: participatory leadership, knowledge management, and inter-disciplinary collaboration. (1) Participatory leadership encourages innovations to originate from the different parts of the organization, and facilitates ownership as well as a culture of excellence. (2) Centers of Excellence are future-oriented in that they are constantly seeking to achieve best practices, informed by the most up-to-date and cutting-edge research and information available. As such, the process by which centres facilitate the flow of knowledge within and outside the organization, or knowledge management, is critical to their success. (3) Such centres also rely on expertise from different disciplines and ‘engaged’ scholarship. This multidisciplinarity leads to improved research productivity and enhances the production of problem-solving innovations. Conclusion Participatory leadership, knowledge management, and inter-disciplinary collaborations are prerequisites to establishing academic CoEs in Africa. Future studies need to extend our findings to understand the processes key to productivity, competitiveness, institutionalization, and sustainability of academic CoEs in Africa.

A Best Practice Framework for Centres of Excellence in Big Data and Artificial Intelligence

This chapter presents a best practice framework for the operation of Big Data and Artificial Intelligence Centres of Excellence (BDAI CoE). The goal of the framework is to foster collaboration and share best practices among existing centres and support the establishment of new Centres of Excellence (CoEs) within Europe. The framework was developed following a phased design science process, starting from a literature review to create an initial framework which was enhanced with the findings of a multi-case study of existing successful CoEs. Each case study involved an in-depth analysis and a series of in-depth interviews with leadership personnel of existing CoEs.The resulting best practice framework models a CoE using open systems theory that comprises input (environment), transformation (CoE) and output (impact). The framework conceptualises the internal operation of the CoE as a set of high-level capabilities including strategy, governance, structure, funding, and people and culture. The core capabilities of the CoE include business development, collaboration, research support services, technical infrastructure, experimentation/demonstration platforms, Intellectual Property (IP) and data protection, education and public engagement, policy outreach, technology and knowledge transfer, and performance and impact assessment. In this chapter we describe the best practice framework for CoEs in big data and AI, including objectives, environment, strategic and operational capabilities, and impact. The chapter outlines how the framework can be used by a CoE to support its strategic direction and operational decisions over time, and how a new CoE can use it in the start-up phase. Based on the analysis of the case studies, the chapter explores the critical success factors of a CoE as defined by a survey of CoE managers. Finally, the chapter concludes with a summary.

Identification of provisional Centres of Excellence for digitisation of European natural science collections

Digitisation of natural science collections is fundamental to the vision for the Distributed System of Scientific Collections (DiSSCo), and given the low proportion of collections digitally accessible, it is proposed that ‘Centres of Excellence’ be developed to accelerate the creation of digital copies of original specimens. Within the ICEDIG project, a team of scientists from across the consortium explored the concept of Centres of Excellence and have constructed a toolset to help identify these centres to support the development of DiSSCo. This report documents this process and describes the toolset.