Researchers at King Abdullah University of Science and Technology (KAUST) have developed a novel genome engineering method for precisely inserting large pieces of genetic information into plants. Published in Nature Biotechnology, this approach allows for targeted placement of large genes into plant genomes without creating DNA breaks, overcoming a long-standing challenge in the field. The method was successfully demonstrated in both tobacco and rice, opening new possibilities for agricultural biotechnology and synthetic biology. Why it matters: This advance could enable the development of more complex traits in crops for improved resilience and sustainable agriculture, and facilitate the use of plants as scalable platforms for producing therapeutics and other valuable compounds.
KAUST researchers have published a study in Nature Genetics detailing genomic analysis of wild rice relatives. The study examined nine tetraploid and two diploid wild relatives of rice, finding significant genetic diversity due to transposable elements. This diversity includes genes that confer resilience to heat, drought, and salinity. Why it matters: These findings can help improve rice yields, introduce rice cultivation to currently untenable regions, and protect rice crops against climate change, especially in the Middle East.
A UAE-based grocery platform is preparing to launch an AI-powered chatbot designed to help residents find the cheapest deals and prices for groceries. This initiative aims to enhance the shopping experience by leveraging artificial intelligence for price comparison. The platform expects the chatbot to streamline the process of finding value for money on everyday essentials. Why it matters: This development signifies the growing adoption of AI in consumer services and e-commerce within the UAE, potentially impacting household budgeting and competitive pricing strategies.
Marcus Engsig from DERC will present a paper at the MATLAB User Group Meeting in Abu Dhabi on October 6. The paper, titled ‘Generalization of Higher Order Methods For Fast Iterative Matrix Inversion Compatible With GPU Acceleration’, discusses a novel approach to matrix inversion using GPUs. The method, named Nested Neumann, achieves 4-100x acceleration compared to standard MATLAB methods for large matrices. Why it matters: This research contributes to faster computation in numerical and physical modeling, crucial for processing large datasets in various scientific and engineering applications in the region.
This paper presents a reinforcement learning framework for optimizing energy pricing in peer-to-peer (P2P) energy systems. The framework aims to maximize the profit of all components in a microgrid, including consumers, prosumers, the service provider, and a community battery. Experimental results on the Pymgrid dataset demonstrate the approach's effectiveness in price optimization, considering the interests of different components and the impact of community battery capacity.
KAUST Ph.D. student Jian You Wang won the outstanding poster award at the 17th International Symposium on Rice Functional Genomics in Taiwan for his work on zaxinone mimics. His research, co-authored by other KAUST researchers and scientists from Japan and Spain, focused on developing easy-to-synthesize compounds that act like zaxinone. Two identified mimics (MiZaxs) significantly increased root growth and biomass in wild-type rice seedlings. Why it matters: This research has implications for developing new rice cultivars with higher yields, addressing global food security challenges.
KAUST's Stochastic Numerics Research Group is developing methods for pricing European options. Their approach, detailed in an upcoming Journal of Computational Finance article, focuses on systematically tuning parameters to achieve accuracy while minimizing computational effort. The goal is to enable automated computation of fair prices for options contracts, similar to how insurance companies determine premiums. Why it matters: This research advances computational finance in the region, potentially improving risk management and investment strategies.
NYU Professor Michael Purugganan presented at KAUST's 2014 Winter Enrichment Program (WEP 2014) on the origins of crop species. He discussed how genome sequencing is improving our understanding of crop evolution, using date fruits collected in Jeddah as an example. His research on rice showed that two varieties, japonica and indica, share a single common ancestor, contrary to previous assumptions. Why it matters: Understanding crop evolution can help adapt crops to changing environments, which is crucial for food security in regions like the Middle East.