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Metamaterials are a special class of engineered materials, designed to have properties not found in nature. Glaucio Paulino, a professor at Princeton University, discusses his work on developing modular chiral origami metamaterials, engineering control approaches and the ways they might benefit society.
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AUSTIN, Texas – A Disaster Recovery Center will open Tuesday, July 15, in Tom Green County to offer face-to-face help to survivors who had damage or losses from the severe storms and flooding in Central Texas.
Homeowners, renters and eligible non-residents may receive FEMA assistance for losses not covered by insurance.Survivors with homeowners’ or renters’ insurance should first file a claim with their insurance company as soon as possible. If your policy does not cover all your damage expenses, you may be eligible for federal assistance.
The Disaster Recovery Center is located at:
Concho Valley Transit Annex
510 N. Chadbourne
San Angelo, TX 76903
Hours: noon to 6 p.m. CT Monday to Friday
FEMA and the U.S. Small Business Administration are supporting the Texas Division of Emergency Management, which is leading efforts to help survivors apply for federal disaster assistance. Center specialists can also identify potential needs and connect survivors with local, state and federal agencies as well as nonprofit organizations and community groups.
Disaster Recovery Centers are accessible to people with disabilities and those with access and functional needs. They are also equipped with assistive technology. If you need a reasonable accommodation or an American Sign Language interpreter, call 833-285-7448 (press 2 for Spanish).
Survivors may visit any Disaster Recovery Center. No appointment is needed.
Here are the ways to apply for FEMA disaster assistance:
For the latest information about the Texas recovery, visit fema.gov/disaster/4879. Follow FEMA
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BOTHELL, Wash. – The Federal Emergency Management Agency (FEMA) authorized the use of federal funds to help with firefighting costs for the Highland Fire burning in Crook County, Oregon.
The state of Oregon’s request for a declaration under FEMA’s Fire Management Assistance Grant (FMAG) program was approved by FEMA Region 10 Acting Administrator Vincent J. Maykovich on Saturday July, 12, 2025, at 10:58 p.m. PT. He determined that the Highland Fire threatened to cause such destruction as would constitute a major disaster. This is the fourth FMAG declaration in 2025 to help fight Oregon wildfires.
At the time of the state’s request, the wildfire threatened homes in and around the community of Prineville Lake Acres. The fire was also threatening roads, infrastructure, utilities, a watershed, and wildlife resources.
FMAGs make funding available to pay up to 75 percent of a state’s eligible firefighting costs for fires that threaten to become major disasters. Eligible items can include expenses for field camps, equipment use, materials, supplies and mobilization and demobilization activities attributed to fighting the fire. These grants do not provide assistance to individual home or business owners and do not cover other infrastructure damage caused by the fire.
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Follow FEMA Region 10 on X and LinkedIn for the latest updates and visit FEMA.gov for more information.
FEMA’s mission is helping people before, during, and after disasters.
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RSS feed source: National Science Foundation
Managing diabetes is a daily challenge faced by nearly 40 million Americans. It involves tracking food intake, timing medication and engaging in physical activity. Getting it wrong can lead to serious health issues; therefore, developing better prediction tools is a vital part of effective diabetes care.
To support better diabetes management, researchers funded by multiple U.S. National Science Foundation grants are developing innovative tools that help patients predict blood sugar levels more precisely without compromising the privacy of their health data. This cutting-edge approach could transform how people with diabetes monitor and manage their condition in real-time.
At the core of this technology is a method called federated learning, which allows artificial intelligence models to be trained across many patients’ devices without sending any personal data to a central server. This setup is ideal for healthcare, where data privacy is paramount and patients often use battery- and memory-limited smart devices. But early federated learning systems struggled to adapt to individual differences, like how people eat, move or react to insulin.
To address this challenge, the research team grouped patients based on their carbohydrate (e.g., sugar and starch) intake levels. The idea is that people who eat in similar ways tend to show similar glucose patterns. By training the AI on these grouped behaviors, the model became more effective at making personalized blood glucose predictions.
To test
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