Food safety is a fundamental right in modern societies. One of the most pressing problems nowadays is the provenance of food and food-related products that citizens consume, mainly due to several food scares and the globalization of food markets, which has resulted in food supply chains that extend beyond nations or even continent boundaries. Food supply networks are characterized by high complexity and a lack of openness. There is a critical requirement for applying novel techniques to verify and authenticate the origin, quality parameters, and transfer/storage details associated with food. This study portrays an end-to-end approach to enhance the security of the food supply chain and thus increase the trustfulness of the food industry. The system aims at increasing the transparency of food supply chain monitoring systems through securing all components that those consist of. A universal information monitoring scheme based on blockchain technology ensures the integrity of collected data, a self-sovereign identity approach for all supply chain actors ensures the minimization of single points of failure, and finally, a security mechanism, that is based on the use of TinyML’s nascent technology, is embedded in monitoring devices to mitigate a significant portion of malicious behavior from actors in the supply chain.
Multiple Sequence Alignment (MSA) is one of the most fundamental methodologies in Bioinformatics and the method capable of arranging DNA or protein sequences to detect regions of similarity. Even on cutting-edge workstations, the MSA procedure requires a significant amount of time regarding its execution time. This paper demonstrates how to utilize Extensa Explorer by Tensilica (Cadence) to create an extended instruction set to meet the requirements of some of the most widely used algorithms in Bioinformatics for MSA analysis. Kalign showed the highest acceleration, reducing Instruction Fetches (IF) and Execution Time (ET) by 30.29 and 43.49 percent, respectively. Clustal had acceleration of 14.2% in IF and 17.9% in ET, whereas Blast had 12.35% in IF and 16.25% in ET.
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