RESUMO
There is great untapped potential for farm mechanization to support rural development initiatives in low- and middle-income countries. As technology transfer of large machinery from high-income countries was ineffective during the 1980s and 90s, mechanization options were developed appropriate to resource poor farmers cultivating small and scattered plots. More recently, projects that aim to increase the adoption of farm machinery have tended to target service providers rather than individual farmers. This paper uses the Scaling Scan tool to assess three project case studies designed to scale different Mechanization Service Provider Models (MSPMs) in Mexico, Zimbabwe, and Bangladesh. It provides a useful framework to assess the gap between international lessons learned on scaling captured in forty tactical questions over ten "scaling ingredients" as perceived by stakeholders involved in the projects, as well as private sector actors and government employees. Although at first sight the case studies seem to successfully reach high numbers of end users, the assessment exposes issues around the sustainable and transformative nature of the interventions. These are highly influenced by the design of the projects and by the environment and context of the intervention areas. Across the three case studies, large-scale adoption of the models was found to be hampered by lack of finance to set up MSPMs and insufficient collaboration among the value chain actors to strengthen and foster Mechanization Service Provider (MSP) entrepreneurs. Applying a scaling perspective on each case study project exposed important lessons on minimizing project dependencies. Positive examples include integration of capacity development materials in vocational training centers in Zimbabwe, promotion of MSPMs by other donors in East Africa and levering of nearly USD six million of private sector investment in appropriate machinery in Bangladesh. On the other hand, there is still a high dependency on the projects in terms of coaching of service providers, facilitating collaboration along the value chain, and provision of leadership and advocacy to address issues at governance level. These results have important implications for similar development interventions aimed at increasing smallholder access to mechanization services at scale and is to our knowledge the first cross-continental assessment of these issues to date.
RESUMO
Chemical reaction networks (CRNs) have been proposed as an abstraction for molecular computing. DNA strand displacement (DSD) reactions are good candidates to realize this endeavor, since DNA strands can be wired to implement the desired dynamic behavior in a test tube. Specialists use simulators to help them design such chemical systems before experimental implementation. In this sense, we present the DNAr package, an alternative open-source tool, developed in R language, for users from multidisciplinary areas. The current version of our tool offers functions to simulate CRNs, convert a formal CRN into a DSD network, interpret results, export to Visual DSD, and create libraries. Here, we use the consensus CRN to show DNAr features and a neural network model to demonstrate scalability, simulating more than 600 chemical reactions in a few minutes.