ABSTRACT
Food and nutrition are a steadfast essential to all living organisms. With specific reference to humans, the sufficient and efficient supply of food is a challenge as the world population continues to grow. Artificial Intelligence (AI) could be identified as a plausible technology in this 5th industrial revolution in bringing us closer to achieving zero hunger by 2030-Goal 2 of the United Nations Sustainable Development Goals (UNSDG). This goal cannot be achieved unless the digital divide among developed and underdeveloped countries is addressed. Nevertheless, developing and underdeveloped regions fall behind in economic resources; however, they harbor untapped potential to effectively address the impending demands posed by the soaring world population. Therefore, this study explores the in-depth potential of AI in the agriculture sector for developing and under-developed countries. Similarly, it aims to emphasize the proven efficiency and spin-off applications of AI in the advancement of agriculture. Currently, AI is being utilized in various spheres of agriculture, including but not limited to crop surveillance, irrigation management, disease identification, fertilization practices, task automation, image manipulation, data processing, yield forecasting, supply chain optimization, implementation of decision support system (DSS), weed control, and the enhancement of resource utilization. Whereas AI supports food safety and security by ensuring higher crop yields that are acquired by harnessing the potential of multi-temporal remote sensing (RS) techniques to accurately discern diverse crop phenotypes, monitor land cover dynamics, assess variations in soil organic matter, predict soil moisture levels, conduct plant biomass modeling, and enable comprehensive crop monitoring. The present study identifies various challenges, including financial, infrastructure, experts, data availability, customization, regulatory framework, cultural norms and attitudes, access to market, and interdisciplinary collaboration, in the adoption of AI for developing nations with their subsequent remedies. The identification of challenges and opportunities in the implementation of AI could ignite further research and actions in these regions; thereby supporting sustainable development.
ABSTRACT
BACKGROUND: We describe the development of a new surgical procedure to be used in the treatment of disruptive brachial plexus (BP) lesions. It is centered on an artificial device designed to assist nerve regeneration by providing a confined and protected environment. Nerve fibers can repair inside the device, while the adverse massive scar-tissue formation is limited to the outside of the device. METHODS: Steps in the development of the procedure were (1) definition of the rationale, (2) design of the device, (3) choice of an in vivo translational model, (4)refinement of the surgical procedure, and (5) performance of an in vivo pilot study as a proof of concept. An interdisciplinary team from several laboratories was involved in this work over a period of 6 years. RESULTS: Results showed the absence of significant scar tissue in the regenerate and the presence of myelinated fibers aligned proximodistally between the stumps. This surgical approach can be seen not only as a definitive treatment but also as an early examination and stabilization before some different surgery will be later performed. It may also be used as additional protection for traditional surgery like end-to-end coaptation. CONCLUSIONS: We conclude that the availability of a suitable device-assisted early treatment, even if not to be considered definitive, could help in addressing the BP lesions at an earlier stage and this may improve the final outcome. Our evidence justifies further experimentation on this approach.
