The energy industry is looking to carbon capture and sequestration to mitigate climate change. That means finding lots of pore space.
They will need thousands of these underground sites to store tens of millions of tons of CO2 to help mitigate climate change.
Scientists are ringing alarm bells about a significant new threat to U.S. water quality: as winters warm due to climate change, they are unleashing large amounts of nutrient pollution into lakes, rivers, and streams.
The first-of-its-kind national study finds that previously frozen winter nutrient pollution—unlocked by rising winter temperatures and rainfall—is putting water quality at risk in 40% of the contiguous U.S., including over 40 states.
Nutrient runoff into rivers and lakes—from phosphorus and nitrogen in fertilizers, manure, animal feed, and more—has affected water quality for decades. However, most research on nutrient runoff in snowy climates has focused on the growing season. Historically, cold temperatures and a continuous snowpack froze nutrients like nitrogen and phosphorous in place until the watershed thawed in the spring, when plants could help absorb excess nutrients.
Deep generative models are a popular data generation strategy used to generate high-quality samples in pictures, text, and audio and improve semi-supervised learning, domain generalization, and imitation learning. Current deep generative models, however, have shortcomings such as unstable training objectives (GANs) and low sample quality (VAEs, normalizing flows). Although recent developments in diffusion and scored-based models attain equivalent sample quality to GANs without adversarial training, the stochastic sampling procedure in these models is sluggish. New strategies for securing the training of CNN-based or ViT-based GAN models are presented.
They suggest backward ODEsamplers (normalizing flow) accelerate the sampling process. However, these approaches have yet to outperform their SDE equivalents. We introduce a novel “Poisson flow” generative model (PFGM) that takes advantage of a surprising physics fact that extends to N dimensions. They interpret N-dimensional data items x (say, pictures) as positive electric charges in the z = 0 plane of an N+1-dimensional environment filled with a viscous liquid like honey. As shown in the figure below, motion in a viscous fluid converts any planar charge distribution into a uniform angular distribution.
A positive charge with z 0 will be repelled by the other charges and will proceed in the opposite direction, ultimately reaching an imaginary globe of radius r. They demonstrate that, in the r limit, if the initial charge distribution is released slightly above z = 0, this rule of motion will provide a uniform distribution for their hemisphere crossings. They reverse the forward process by generating a uniform distribution of negative charges on the hemisphere, then tracking their path back to the z = 0 planes, where they will be dispersed as the data distribution.
Professor Vincent Pasque and his colleagues at KU Leuven have used stem cells to create a new kind of human cell in the lab. The new cells closely mirror their natural counterparts in early human embryos. As a result, scientists are better able to understand what occurs just after an embryo implants in the womb. The was recently published in the journal Cell Stem Cell.
A human embryo implants in the womb around seven days after fertilization if everything goes correctly. Due to technological and ethical constraints, the embryo becomes unavailable for study at that point. That is why scientists have already created stem cell models for various kinds of embryonic and extraembryonic cells in order to investigate human development in a dish.
Tesla announced today that it is moving away from using ultrasonic sensors in its suite of Autopilot sensors in favor of its camera-only “Tesla Vision” system.
Last year, Tesla announced it would transition to its “Tesla Vision” Autopilot without radar and start producing vehicles without a front-facing radar.
Originally, the suite of Autopilot sensors – which Tesla claimed would include everything needed to achieve full self-driving capability eventually – included eight cameras, a front-facing radar, and several ultrasonic sensors all around its vehicles.
This metaverse meme video is about wojak who grows old in a metaverse. From the moment he is still a child and has his first school day, he already lives through his vr glasses. His school is in the metaverse, as well as his friends. Years later, he starts doubting about how “normal” living meta actually is. Didn’t people maybe have a better life back when there was no metaverse? When you did stuff offline? Who knows…
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A team of Penn State engineers has created a stretchy, wearable synaptic transistor that could turn robotics and wearable devices smarter. The device developed by the team works like neurons in the brain, sending signals to some cells and inhibiting others to enhance and weaken the devices’ memories.
The research was led by Cunjiang Yu, Dorothy Quiggle Career Development Associate Professor of Engineering Science and Mechanics and associate professor of biomedical engineering and of materials science and engineering.
The research was published in Nature Electronics.
The average annual pay hike for data science professionals is between 20–30 per cent compared to 15–20 per cent for professionals from other backgrounds, the report says.
STOCKHOLM — Three scientists jointly won this year’s Nobel Prize in physics Tuesday for proving that tiny particles could retain a connection with each other even when separated, a phenomenon once doubted but now being explored for potential real-world applications such as encrypting information.
Frenchman Alain Aspect, American John F. Clauser and Austrian Anton Zeilinger were cited by the Royal Swedish Academy of Sciences for experiments proving the “totally crazy” field of quantum entanglements to be all too real. They demonstrated that unseen particles, such as photons, can be linked, or “entangled,” with each other even when they are separated by large distances.
It all goes back to a feature of the universe that even baffled Albert Einstein and connects matter and light in a tangled, chaotic way.
