Lifeboat Foundation

Researchers at McMaster University have developed a promising new cancer immunotherapy that uses cancer-killing cells genetically engineered outside the body to find and destroy malignant tumors.

The modified “natural killer” cells can differentiate between cancer cells and healthy cells that are often intermingled in and around tumors, destroying only the targeted cells.

The natural killer cells’ ability to distinguish the target cells, even from healthy cells that bear similar markers, brings new promise to this branch of immunotherapy, say members of the research team behind a paper published in the current issue of the journal iScience, newly posted on the PubMed database.

The speech sent by **Jan Wörner — former Director General of ESA -** for the Inaugural Opening Session of the 2021 Space Renaissance Congress.

Jan couldn’t present live, however he kindly sent us his speech, that we are nonored and proud to publish and add to the Acta of the Congress.

Continue reading “Jan Wörner KeyNote Speech to the 2021 Space Renaissance Congress” »

Supermoons typically occur once or twice a year when the Moon is full and at its closest point to the Earth. Don’t miss the opportunity to see the next one.

Twenty years after the publication of their game-changing book “Rare Earth,” Ward and Brownlee argue that planets like Earth are likely as rare as ever.

Washington — As the U.S. continues to navigate its way through the COVID-19 pandemic, Dr. Scott Gottlieb, the former commissioner of the Food and Drug Administration, said areas of the country could experience “very dense outbreaks” with the concerning Delta variant continuing to circulate.

“It’s going to be hyper-regionalized, where there are certain pockets of the country [where] we can have very dense outbreaks,” Gottlieb said Sunday on CBS News’ “Face the Nation.”

The most vulnerable areas continue to be those with low vaccination rates and low rates of immunity from prior infections. According to the Centers for Disease Control and Prevention, many southern states have vaccination rates that lag behind the national average.

The challenges of making AI work at the edge—that is, making it reliable enough to do its job and then justifying the additional complexity and expense of putting it in our devices—are monumental. Existing AI can be inflexible, easily fooled, unreliable and biased. In the cloud, it can be trained on the fly to get better—think about how Alexa improves over time. When it’s in a device, it must come pre-trained, and be updated periodically. Yet the improvements in chip technology in recent years have made it possible for real breakthroughs in how we experience AI, and the commercial demand for this sort of functionality is high.

AI is moving from data centers to devices, making everything from phones to tractors faster and more private. These newfound smarts also come with pitfalls.

Satellite imagery is becoming ubiquitous. Research has demonstrated that artificial intelligence applied to satellite imagery holds promise for automated detection of war-related building destruction. While these results are promising, monitoring in real-world applications requires high precision, especially when destruction is sparse and detecting destroyed buildings is equivalent to looking for a needle in a haystack. We demonstrate that exploiting the persistent nature of building destruction can substantially improve the training of automated destruction monitoring. We also propose an additional machine-learning stage that leverages images of surrounding areas and multiple successive images of the same area, which further improves detection significantly. This will allow real-world applications, and we illustrate this in the context of the Syrian civil war.

Existing data on building destruction in conflict zones rely on eyewitness reports or manual detection, which makes it generally scarce, incomplete, and potentially biased. This lack of reliable data imposes severe limitations for media reporting, humanitarian relief efforts, human-rights monitoring, reconstruction initiatives, and academic studies of violent conflict. This article introduces an automated method of measuring destruction in high-resolution satellite images using deep-learning techniques combined with label augmentation and spatial and temporal smoothing, which exploit the underlying spatial and temporal structure of destruction. As a proof of concept, we apply this method to the Syrian civil war and reconstruct the evolution of damage in major cities across the country. Our approach allows generating destruction data with unprecedented scope, resolution, and frequency—and makes use of the ever-higher frequency at which satellite imagery becomes available.

Investigators at Cedars-Sinai and UC San Diego found that a synthetic compound given orally protected the liver against injury in an animal model for alcoholic hepatitis.

The study, co-authored by Dr. Ekihiro Seki, was published in the Proceedings of the Na… See More.

The most prevalent forms of ALD are fatty liver, alcoholic hepatitis and cirrhosis. Corticosteroids are the only treatment option for alcoholic hepatitis, or chronic inflammation of the liver, despite little evidence of long-term efficacy and considerable adverse side effects.

Continue reading “Compound Tested for Alcoholic Liver Disease” »

The promise of 5G Internet of Things (IoT) networks requires more scalable and robust communication systems—ones that deliver drastically higher data rates and lower power consumption per device.

Backscatter radios—passive sensors that reflect rather than radiate energy—are known for their low-cost, low-complexity, and battery-free operation, making them a potential key enabler of this future although they typically feature low data rates and their performance strongly depends on the surrounding environment.

Researchers at the Georgia Institute of Technology, Nokia Bell Labs, and Heriot-Watt University have found a low-cost way for backscatter radios to support high-throughput communication and 5G-speed Gb/sec data transfer using only a single transistor when previously it required expensive and multiple stacked transistors.