Geothermal Resource Type
300-degree hot springs hiding under the frozen Antarctic sea
A robotic sub explored a hidden world 1,300 meters under Antarctica. More information Adding us as a Preferred Source in Google by using this link indicates that you would like to see more of our content in Google News results. Breakthroughs, discoveries, and DIY tips sent six days a week. The Antarctic sea, where glaciers drift across the surface. What kind of world lies 1,300 meters below the surface?
Conformal Prediction with Time-Series Data via Sequential Conformalized Density Regions
We propose a new conformal prediction method for time-series data with a guaranteed asymptotic conditional coverage rate, Sequential Conformalized Density Regions (SCDR), which is flexible enough to produce both prediction intervals and disconnected prediction sets, signifying the emergence of bifurcations. Our approach uses existing estimated conditional highest density predictive regions to form initial predictive regions. We then use a quantile random forest conformal adjustment to provide guaranteed coverage while adaptively changing to take the non-exchangeable nature of time-series data into account. We show that the proposed method achieves the guaranteed coverage rate asymptotically under certain regularity conditions. In particular, the method is doubly robust -- it works if the predictive density model is correctly specified and/or if the scores follow a nonlinear autoregressive model with the correct order specified. Simulations reveal that the proposed method outperforms existing methods in terms of empirical coverage rates and set sizes. We illustrate the method using two real datasets, the Old Faithful geyser dataset and the Australian electricity usage dataset. Prediction sets formed using SCDR for the geyser eruption durations include both single intervals and unions of two intervals, whereas existing methods produce wider, less informative, single-interval prediction sets.
World's largest acidic geyser erupts in Yellowstone after years of silence - sparking fears the supervolcano could be next
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World's largest acidic geyser erupts for first time since 2020
Environment Conservation World's largest acidic geyser erupts for first time since 2020 Echinus Geyser in Yellowstone National Park is in one of the park's hottest and most dynamic regions. Breakthroughs, discoveries, and DIY tips sent six days a week. The world's largest acidic geyser is erupting for the first time in six years. Yellowstone National Park's Echinus Geyser is part of the very active Norris Geyser Basin in Wyoming. In early February, the geyser began spewing out acid and water up to 30 feet into the air.
5,000-year-old bacteria thawed in Romanian ice cave
Breakthroughs, discoveries, and DIY tips sent six days a week. Whether it's the ocean's deepest hydrothermal vents or tall mountain peaks, bacteria is likely surviving and thriving. Ice caves can host a wide variety of microorganisms and offer biologists a bevy of genetic diversity that still has to be studied. And it could help save lives. A team of scientists in Romania tested antibiotic resistance profiles with a bacterial strain that was hidden in a 5,000-year-old layer of ice inside an underground ice cave.
The Download: LLM confessions, and tapping into geothermal hot spots
OpenAI is testing a new way to expose the complicated processes at work inside large language models. Researchers at the company can make an LLM produce what they call a confession, in which the model explains how it carried out a task and (most of the time) own up to any bad behavior. Figuring out why large language models do what they do--and in particular why they sometimes appear to lie, cheat, and deceive--is one of the hottest topics in AI right now. If this multitrillion-dollar technology is to be deployed as widely as its makers hope it will be, it must be made more trustworthy. OpenAI sees confessions as one step toward that goal. Sometimes geothermal hot spots are obvious, marked by geysers and hot springs on Earth's surface.
How AI is uncovering hidden geothermal energy resources
Zanskar used AI tools to identify a site that could host a commercial power plant. Zanskar used AI tools to help revive a New Mexico geothermal plant. Now, the company found a hotspot that could support a new power plant. Sometimes geothermal hot spots are obvious, marked by geysers and hot springs on the planet's surface. But in other places, they're obscured thousands of feet underground. Now AI could help uncover these hidden pockets of potential power.
A Startup Says It Has Found a Hidden Source of Geothermal Energy
Zanskar uses AI to identify hidden geothermal systems--and claims it has found one that could fuel a power plant, the first such discovery by industry in decades. A geothermal startup said Thursday that it has hit gold in Nevada--metaphorically speaking. Zanskar, which uses AI to find hidden geothermal resources deep underground, says that it has identified a new commercially viable site for a potential power plant. The discovery, the company claims, is the first of its kind made by the industry in decades. The find is the culmination of years of research on how to find these resources--and points to the growing promise of geothermal energy .
Underwater Visual-Inertial-Acoustic-Depth SLAM with DVL Preintegration for Degraded Environments
Ding, Shuoshuo, Zhang, Tiedong, Jiang, Dapeng, Lei, Ming
Abstract--Visual degradation caused by limited visibility, insufficient lighting, and feature scarcity in underwater environments presents significant challenges to visual-inertial simultaneous localization and mapping (SLAM) systems. The key innovation lies in the tight integration of four distinct sensor modalities to ensure reliable operation, even under degraded visual conditions. To mitigate DVL drift and improve measurement efficiency, we propose a novel velocity-bias-based DVL preintegration strategy. At the frontend, hybrid tracking strategies and acoustic-inertial-depth joint optimization enhance system stability. Additionally, multi-source hybrid residuals are incorporated into a graph optimization framework. Extensive quantitative and qualitative analyses of the proposed system are conducted in both simulated and real-world underwater scenarios. The results demonstrate that our approach outperforms current state-of-the-art stereo visual-inertial SLAM systems in both stability and localization accuracy, exhibiting exceptional robustness, particularly in visually challenging environments. UMAN activities in the fields of ocean engineering and marine science are increasing steadily, encompassing scientific expeditions to study underwater hydrothermal vents and archaeological sites, inspections and maintenance of subsea pipelines and reservoirs, and salvage operations for wrecked aircraft and vessels. Shuoshuo Ding, Tiedong Zhang and Dapeng Jiang are with School of Ocean Engineering and T echnology & Southern Marine science and Engineering Guangdong Laboratory (Zhuhai), Sun Y at-sen University, Zhuhai 519082, China, with Guangdong Provincial Key Laboratory of Information T echnology for Deep Water Acoustics, Zhuhai 519082, China, and also with Key Laboratory of Comprehensive Observation of Polar Environment (Sun Y at-sen University), Ministry of Education, Zhuhai 519082, China (e-mail: dingshsh5@mail2.sysu.edu.cn,
Yellowstone employees recover over 300 hats from hydrothermal areas
Be sure to hold on to your hats (and pizza) when near a boiling hot vent. Breakthroughs, discoveries, and DIY tips sent every weekday. No, it's your hat, ripped off your head by a gust of wind, spiraling off into the unknown. It's happened to the best of us. The only thing left to do is purchase another one before your face gets sunburnt .