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A new method for predicting underwater landslides may improve the resilience of offshore facilities.
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Author: WeWorldMedia-admin
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Each year, preeclampsia—a life-threatening pregnancy complication—affects nearly 1 in 25 expectant mothers in the United States. Emerging suddenly after 20 weeks of pregnancy, it can lead to dangerously high blood pressure, premature birth, and long-term health issues for both mother and baby. Despite its severity, the root causes of preeclampsia remain poorly understood, and treatment options are limited.
Currently, the only effective treatment for preeclampsia is early delivery of the placenta, which often leads to premature birth and associated health risks for the baby. While researchers know the placenta plays a central role in the disease, the exact causes of its dysfunction remain unclear. This lack of understanding makes preeclampsia difficult to predict, prevent, or treat effectively.
Researchers at UC San Diego are tackling these challenges with help from NSF-supported computational resources. The team leveraged advanced computing systems like the San Diego Supercomputer Center’s Expanse to conduct large-scale RNA sequencing analysis to compare placental tissue from healthy and preeclamptic pregnancies—processing terabytes of next-generation sequencing data to identify genes that behave differently in the disease.
Expanse also enabled the team to develop a model system of preeclampsia using induced pluripotent stem cells (iPSCs), which allows scientists to recreate the disease in the lab and observe how stress conditions like low oxygen affect placental development. By replicating these abnormal conditions, the team identified biological pathways—like inflammation and
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In-brief analysis
May 30, 2025
Data source: Wards Intelligence
About 22% of light-duty vehicles sold in the first quarter of the year in the United States were hybrid, battery electric, or plug-in hybrid vehicles, up from about 18% in the first quarter of 2024. Among those categories, hybrid electric vehicles have continued to gain market share while battery electric vehicles and plug-in hybrid vehicles have remained relatively flat, according to estimates from Wards Intelligence.
These different vehicle types affect the broader energy sector in different ways. Battery electric vehicles and plug-in hybrid vehicles can consume electricity from isolated power sources or, more commonly, from the grid. So, their use can affect electricity demand. By comparison, hybrid electric vehicles do not have plugs, so they don’t directly affect grid-delivered electricity demand.
Data
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Description:
Lightweight fibre-reinforced composites are vital in enabling more efficient wind turbines and making cars lighter. Composite structures face large safety factors, which can make them heavier and more expensive. These large factors are required due to the early damage initiation and the challenges in predicting their damage development. This project will address both aspects with a focus on off-axis cracks. These cracks are usually the first significant damage that initiates upon loading the composite in tension or bending, and are hence a key reason for the large safety factors. Despite their importance, most models for off-axis cracks are limited to 90° plies and 2D. Such models have led to a basic understanding of the initiation phase on the surface, but a very limited understanding of the propagation phase in the bulk of the material.
The key challenge of this PhD project is
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