The coronavirus disease (COVID-19) breakout had an unimaginable worldwide effect in the 21st century, claiming millions of lives and putting a huge burden on the global economy. The potential developments in vaccine technologies following the determination of the genetic sequence of SARS-CoV-2 and the increasing global efforts to bring potential vaccines and therapeutics into the market for emergency use have provided a small bright spot to this tragic event. Several intriguing vaccine candidates have been developed using recombinant technology, genetic engineering, and other vaccine development technologies. In the last decade, a vast amount of the vaccine development process has diversified towards the usage of viral vector-based vaccines. The immune response elicited by such vaccines is comparatively higher than other approved vaccine candidates that require a booster dose to provide sufficient immune protection. The non-replicating adenoviral vectors are promising vaccine carriers for infectious diseases due to better yield, cGMP-friendly manufacturing processes, safety, better efficacy, manageable shipping, and storage procedures. As of April 2022, the WHO has approved a total of 10 vaccines around the world for COVID-19 (33 vaccines approved by at least one country), among which three candidates are adenoviral vector-based vaccines. This review sheds light on the developmental summary of all the adenoviral vector-based vaccines that are under emergency use authorization (EUA) or in the different stages of development for COVID-19 management.

A unique three-dimensional packing problem with non-convex parts and without a gravity constraint can be defined in a selective laser sintering rapid prototyping machine. The goal for the packing task is to pack the parts to be manufactured as tightly as possible to maximize volume and machine time utilization. A genetic algorithm is used as a search engine to find a good packing pattern for parts. Each individual in a population represents one packing solution. The chromosomal representation is a three-dimensional ordered list of integers where each sublist has a different allele set. A fitness function simulates the packing of parts and also evaluates the quality of a solution. To calculate part intersections, the fitness function uses methods common in computational geometry. Due to the chromosome structure used, there is a lack of genetic material in the population. Methods to introduce new material into the population are defined and tested. Experiments with more difficult packing problems, where all parts are complex in shape, prove that the developed genetic algorithm is robust and able to find a good solution in most problem instances.