This paper examines the relationship between COVID-19 spread and weather patterns across 89 cities in Saudi Arabia using machine learning. The study uses daily COVID-19 case reports from the Saudi Ministry of Health and historical weather data. The results indicate that temperature and wind speed have the strongest correlation with the spread of COVID-19, with a random forest model achieving the best performance.
Researchers studied user lifetime prediction in the location-based social network Jodel within Saudi Arabia, leveraging its disjoint communities. Machine learning models, particularly Random Forest, were trained to predict user lifetime as a regression and classification problem. A single countrywide model generalizes well and performs similarly to community-specific models.
KAUST researchers, in collaboration with the Salk Institute and Altos Labs, have identified a class of RNA (LINE-1) that, when compromised, leads to accelerated aging, as seen in progeria. They devised an antisense RNA strategy to block the aberrant function of L1 RNA, reversing the disease in mice and patient-derived cells. Published in Science Translational Medicine, the research suggests that targeting LINE-1 RNA could treat progeroid syndromes and other age-related diseases. Why it matters: This RNA-based approach provides a potential therapeutic avenue for treating premature aging diseases and extending human health span in the region and globally.
KAUST researchers are studying coral reefs in the Northern Red Sea, which exhibit unusual heat tolerance, surviving temperatures 5°C above the mean summer maximum. This resilience makes them a potential refuge for coral, offering a "climate change insurance" for the next 100 years. Researchers aim to understand the mechanisms behind this thermotolerance to aid coral conservation efforts globally. Why it matters: Understanding and preserving these unique coral reefs could provide crucial insights and strategies for protecting coral ecosystems worldwide in the face of rising ocean temperatures.
A new framework for constructing confidence sets for causal orderings within structural equation models (SEMs) is presented. It leverages a residual bootstrap procedure to test the goodness-of-fit of causal orderings, quantifying uncertainty in causal discovery. The method is computationally efficient and suitable for medium-sized problems while maintaining theoretical guarantees as the number of variables increases. Why it matters: This offers a new dimension of uncertainty quantification that enhances the robustness and reliability of causal inference in complex systems, but there is no indication of connection to the Middle East.
This study investigates the correlation between Google Trends data for COVID-19 symptoms and the actual number of COVID-19 cases in Saudi Arabia between March and October 2020. The researchers found that searches for "cough" and "sore throat" were most frequent, while "loss of smell", "loss of taste", and "diarrhea" showed the highest correlation with confirmed cases. The study concludes that Google searches can serve as a supplementary surveillance tool for monitoring the spread of COVID-19 in Saudi Arabia. Why it matters: The research demonstrates the potential of using readily available digital data to augment traditional surveillance methods for public health monitoring in the region.
In a 2018 KAUST lecture, MIT professor Kamal Youcef-Toumi discussed the case of Ordos Kangbashi, a Chinese city designed for a million residents that became a near-ghost town. Despite government incentives, the city struggled due to an economic downturn and lack of social and economic balance. Youcef-Toumi emphasized the importance of the public realm and a balance between social and economic development for successful cities. Why it matters: The analysis provides insights relevant to urban planning in Saudi Arabia and the broader GCC region, where new cities and megaprojects are being developed.
Mona Alsomali, who graduated from KAUST in 2016 with a Ph.D. in bioscience-microbial genomics, is now a senior microbiologist. She is currently employed at the Dow Middle East Innovation Center (MEIC)/KAUST. The center is located at KAUST. Why it matters: This highlights KAUST's role in producing skilled graduates who contribute to scientific innovation in the region.