Codons
Researchers from Dali University, People's Republic of China, have published a study on the codon usage bias (CUB) in Dendrobium orchids, highlighting the essential role it plays in genetic engineering and breeding. The study analyzed the chloroplast genomes of 49 Dendrobium species and found that natural selection is
Algorithms
Researchers from Southern Technical University, in collaboration with Mahmood A. Al-Shareeda and Ahmad Taher Azar, have developed a novel hybrid application mapping framework that integrates Genetic Algorithm (GA) with Reinforcement Learning (RL) to optimize task allocation in 2D Network-on-Chip based Multiprocessor System-on-Chip (NoC-based MPSoC) architectures. This innovative approach, called Reinforcement
Codons
Researchers from Dali University, People's Republic of China, have published a study on the codon usage bias (CUB) in Dendrobium orchids, highlighting the essential role it plays in genetic engineering and breeding. The study analyzed the chloroplast genomes of 49 Dendrobium species and found that natural selection is
Algorithms
Researchers from Szechenyi Istvan University have developed an advanced optimization methodology for truss structures, addressing both elasto-plastic design cases and purely elastic scenarios. The study, published in Fracture and Structural Integrity, focuses on minimizing structural weight while meeting all structural performance criteria. The researchers used a genetic algorithm to determine
Genetic research
Researchers from Dali University, People's Republic of China, have published a study on the codon usage bias (CUB) in Dendrobium orchids, highlighting the essential role it plays in genetic engineering and breeding. The study analyzed the chloroplast genomes of 49 Dendrobium species and found that natural selection is
Algorithms
Researchers from Southern Technical University, in collaboration with Mahmood A. Al-Shareeda and Ahmad Taher Azar, have developed a novel hybrid application mapping framework that integrates Genetic Algorithm (GA) with Reinforcement Learning (RL) to optimize task allocation in 2D Network-on-Chip based Multiprocessor System-on-Chip (NoC-based MPSoC) architectures. This innovative approach, called Reinforcement
Genetic engineering
Researchers at the Instituto de Biologia Molecular y Celular de Plantas have developed a novel platform for using synthetic trans-acting small interfering RNAs (syn-tasiRNAs) to silence genes in tomato plants. This breakthrough has the potential to improve crop yields and disease resistance in tomatoes, one of the world's
Genes
Researchers at Oak Ridge National Laboratory in Tennessee have made groundbreaking discoveries in the field of gene editing, specifically in multiplex CRISPR editing for plant genome engineering. This innovative approach enables the simultaneous targeting of multiple genes, regulatory elements, or chromosomal regions, leading to the acceleration of trait stacking and
Genetic engineering
Research led by the National Key Facility for Crop Gene Resources and Genetic Improvement has made a significant breakthrough in the field of genome editing. By fusing deaminases with the CRISPR/Cas system, base editing enables precise single-base modifications of DNA. This innovation has vast potential for crop improvement, and
Genetic research
Researchers in the field of mechanical engineering have made a significant breakthrough in optimizing the machining operation sequence problem, a crucial task in computer-aided process planning. The study proposes a hybrid approach called the integrated genetic and simulated annealing (IGSA) algorithm, which aims to reduce tool changes and machine setup
Genetic research
Researchers at Liaoning Technical University in China have published a new study on the demand-based regulation of mine airflow using a niche genetic algorithm. The study's findings suggest that this approach can effectively regulate mine ventilation systems, reducing energy consumption and ensuring the safety of the underground environment.
Genetic research
Researchers in the field of mechanical engineering have made a significant breakthrough in optimizing the machining operation sequence problem, a crucial task in computer-aided process planning. The study proposes a hybrid approach called the integrated genetic and simulated annealing (IGSA) algorithm, which aims to reduce tool changes and machine setup
