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TAMPA, Fla. — Mandala Space Ventures, a Californian venture studio and incubator, announced July 8 the nine United Kingdom-based startups participating in its UK Space Agency-funded accelerator program this fall.

The eight-week virtual course starts Sept. 3 and culminates with an in-person investor pitch day at the California Institute of Technology (Caltech) in Pasadena, California.

The SoCal-UK Space Accelerator creates a “transatlantic portal for great ideas from the U.K.,” said Mandala founder and CEO Leon Alkalai, helping prepare them for venture capital and access to the U.S. market.

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“Sulfur is a vital element for building more complex molecules, and—like carbon, nitrogen, oxygen, and phosphate—scientists need to study it more to fully understand how planets are made and what they’re made of,” said Dr. Guangwei Fu.

How do exoplanets smell? This is what a recent study published in Nature hopes to address as a team of researchers investigated the atmosphere of HD 189,733 b, which is a “hot Jupiter” located approximately 64 light-years from Earth, discovering this unique exoplanet’s atmosphere contains hydrogen sulfide, which is a byproduct of sulfur and known for its rotten egg-like smell. This discovery holds the potential to help astronomers better understand the atmospheric composition of exoplanets and how these compositions can drive the interior processes of these exoplanets, as well.

Artist’s illustration of HD 189,733 b. (Credit: Roberto Molar Candanosa/Johns Hopkins Univeristy)

“Hydrogen sulfide is a major molecule that we didn’t know was there,” said Dr. Guangwei Fu, who is an assistant research scientist at Johns Hopkins University and lead author of the study. “We predicted it would be, and we know it’s in Jupiter, but we hadn’t really detected it outside the solar system. We’re not looking for life on this planet because it’s way too hot but finding hydrogen sulfide is a steppingstone for finding this molecule on other planets and gaining more understanding of how different types of planets form.”

Continue reading “Exoplanet’s Rotten Egg Smell Revealed by Webb Telescope” | >

The largest animals do not have proportionally bigger brains — with humans bucking this trend — a new study published in Nature Ecology and Evolution has revealed.

Researchers at the University of Reading and Durham University collected an enormous dataset of brain and body sizes from around 1,500…

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The production of MegaPacks at the facility in Lathrop, California is highly profitable and the market for MegaPacks is expected to grow as the price of cells comes down Questions to inspire discussion How much power does the facility produce daily? —The facility produces a lot of power daily, with the output constantly changing.

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T-cell transfer therapy is a type of immunotherapy that makes your own immune cells better able to attack cancer. There are two main types of T-cell transfer therapy: tumor-infiltrating lymphocytes (or TIL) therapy and CAR T-cell therapy. Both involve collecting your own immune cells, growing large numbers of these cells in the lab, and then giving the cells back to you through a needle in your vein. T-cell transfer therapy is also called adoptive cell therapy, adoptive immunotherapy, and immune cell therapy.

The process of growing your T cells in the lab can take 2 to 8 weeks. During this time, you may have treatment with chemotherapy and, maybe, radiation therapy to get rid of other immune cells. Reducing your immune cells helps the transferred T cells to be more effective. After these treatments, the T cells that were grown in the lab will be given back to you via a needle in your vein.

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As artificial intelligence (AI) becomes increasingly ubiquitous in business and governance, its substantial environmental impact — from significant increases in energy and water usage to heightened carbon emissions — cannot be ignored. By 2030, AI’s power demand is expected to rise by 160%. However, adopting more sustainable practices, such as utilizing foundation models, optimizing data processing locations, investing in energy-efficient processors, and leveraging open-source collaborations, can help mitigate these effects. These strategies not only reduce AI’s environmental footprint but also enhance operational efficiency and cost-effectiveness, balancing innovation with sustainability.

Page-utils class= article-utils—vertical hide-for-print data-js-target= page-utils data-id= tag: blogs.harvardbusiness.org, 2007/03/31:999.386782 data-title= How Companies Can Mitigate AI’s Growing Environmental Footprint data-url=/2024/07/how-companies-can-mitigate-ais-growing-environmental-footprint data-topic= Environmental sustainability data-authors= Christina Shim data-content-type= Digital Article data-content-image=/resources/images/article_assets/2024/06/Jul24_04_1298348302-383x215.jpg data-summary=

Practical steps for reducing AI’s surging demand for water and energy.

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Toronto, Ontario —A new ultra-high-performance brain PET system allows for the direct measurement of brain nuclei as never before seen or quantified. With its ultra-high sensitivity and resolution, the NeuroEXPLORER provides exceptional brain PET images and has the potential to spur advances in the treatment of many brain diseases. This research was presented at the 2024 Society of Nuclear Medicine and Molecular Imaging (SNMMI) Annual Meeting, and the grouping of images highlighting targeted tracer uptake in specific brain nuclei has been selected as the 2024 SNMMI Henry N. Wagner, Jr., Image of the Year.

Each year, SNMMI chooses an image that best exemplifies the most promising advances in the field of nuclear medicine and molecular imaging. The state-of-the-art technologies captured in these images demonstrate the capacity to improve patient care by detecting disease, aiding diagnosis, improving clinical confidence, and providing a means of selecting appropriate treatments. This year, the SNMMI Image of the Year was chosen from more than 1,500 abstracts submitted for the meeting.

The image quality of PET systems has improved in recent years, mostly by increases in sensitivity, including enhanced time-of-flight capabilities. However, these systems have shown only minimal improvement in intrinsic resolution. To address these issues, researchers designed the NeuroEXPLORER PET scanner with a focus on ultra-high sensitivity and resolution, as well as continuous head motion correction.

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“We want to build tools that can make biology programmable,” says Alex Rives, the company’s chief scientist, who was part of Meta’s efforts to apply AI to biological data.

EvolutionaryScale’s AI tool, called ESM3, is what’s known as a protein language model. It was trained on more than 2.7 billion protein sequences and structures, as well as information about these proteins’ functions. The model can be used to create proteins to specifications provided by users, akin to the text spit out by chatbots such as ChatGPT.

“It’s going to be one of the AI models in biology that everybody’s paying attention to,” says Anthony Gitter, a computational biologist at the University of Wisconsin–Madison.

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